Fisher classifier and its probability of error estimation
Chittineni, C. B.
1979-01-01
Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.
Selection of anchor values for human error probability estimation
International Nuclear Information System (INIS)
Buffardi, L.C.; Fleishman, E.A.; Allen, J.A.
1989-01-01
There is a need for more dependable information to assist in the prediction of human errors in nuclear power environments. The major objective of the current project is to establish guidelines for using error probabilities from other task settings to estimate errors in the nuclear environment. This involves: (1) identifying critical nuclear tasks, (2) discovering similar tasks in non-nuclear environments, (3) finding error data for non-nuclear tasks, and (4) establishing error-rate values for the nuclear tasks based on the non-nuclear data. A key feature is the application of a classification system to nuclear and non-nuclear tasks to evaluate their similarities and differences in order to provide a basis for generalizing human error estimates across tasks. During the first eight months of the project, several classification systems have been applied to a sample of nuclear tasks. They are discussed in terms of their potential for establishing task equivalence and transferability of human error rates across situations
Human error probability estimation using licensee event reports
International Nuclear Information System (INIS)
Voska, K.J.; O'Brien, J.N.
1984-07-01
Objective of this report is to present a method for using field data from nuclear power plants to estimate human error probabilities (HEPs). These HEPs are then used in probabilistic risk activities. This method of estimating HEPs is one of four being pursued in NRC-sponsored research. The other three are structured expert judgment, analysis of training simulator data, and performance modeling. The type of field data analyzed in this report is from Licensee Event reports (LERs) which are analyzed using a method specifically developed for that purpose. However, any type of field data or human errors could be analyzed using this method with minor adjustments. This report assesses the practicality, acceptability, and usefulness of estimating HEPs from LERs and comprehensively presents the method for use
Development of an integrated system for estimating human error probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, J.L.; Hahn, H.A.; Morzinski, J.A.
1998-12-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This project had as its main objective the development of a Human Reliability Analysis (HRA), knowledge-based expert system that would provide probabilistic estimates for potential human errors within various risk assessments, safety analysis reports, and hazard assessments. HRA identifies where human errors are most likely, estimates the error rate for individual tasks, and highlights the most beneficial areas for system improvements. This project accomplished three major tasks. First, several prominent HRA techniques and associated databases were collected and translated into an electronic format. Next, the project started a knowledge engineering phase where the expertise, i.e., the procedural rules and data, were extracted from those techniques and compiled into various modules. Finally, these modules, rules, and data were combined into a nearly complete HRA expert system.
BAYES-HEP: Bayesian belief networks for estimation of human error probability
International Nuclear Information System (INIS)
Karthick, M.; Senthil Kumar, C.; Paul, Robert T.
2017-01-01
Human errors contribute a significant portion of risk in safety critical applications and methods for estimation of human error probability have been a topic of research for over a decade. The scarce data available on human errors and large uncertainty involved in the prediction of human error probabilities make the task difficult. This paper presents a Bayesian belief network (BBN) model for human error probability estimation in safety critical functions of a nuclear power plant. The developed model using BBN would help to estimate HEP with limited human intervention. A step-by-step illustration of the application of the method and subsequent evaluation is provided with a relevant case study and the model is expected to provide useful insights into risk assessment studies
A framework to estimate probability of diagnosis error in NPP advanced MCR
International Nuclear Information System (INIS)
Kim, Ar Ryum; Kim, Jong Hyun; Jang, Inseok; Seong, Poong Hyun
2018-01-01
Highlights: •As new type of MCR has been installed in NPPs, the work environment is considerably changed. •A new framework to estimate operators’ diagnosis error probabilities should be proposed. •Diagnosis error data were extracted from the full-scope simulator of the advanced MCR. •Using Bayesian inference, a TRC model was updated for use in advanced MCR. -- Abstract: Recently, a new type of main control room (MCR) has been adopted in nuclear power plants (NPPs). The new MCR, known as the advanced MCR, consists of digitalized human-system interfaces (HSIs), computer-based procedures (CPS), and soft controls while the conventional MCR includes many alarm tiles, analog indicators, hard-wired control devices, and paper-based procedures. These changes significantly affect the generic activities of the MCR operators, in relation to diagnostic activities. The aim of this paper is to suggest a framework to estimate the probabilities of diagnosis errors in the advanced MCR by updating a time reliability correlation (TRC) model. Using Bayesian inference, the TRC model was updated with the probabilities of diagnosis errors. Here, the diagnosis error data were collected from a full-scope simulator of the advanced MCR. To do this, diagnosis errors were determined based on an information processing model and their probabilities were calculated. However, these calculated probabilities of diagnosis errors were largely affected by context factors such as procedures, HSI, training, and others, known as PSFs (Performance Shaping Factors). In order to obtain the nominal diagnosis error probabilities, the weightings of PSFs were also evaluated. Then, with the nominal diagnosis error probabilities, the TRC model was updated. This led to the proposal of a framework to estimate the nominal probabilities of diagnosis errors in the advanced MCR.
International Nuclear Information System (INIS)
Comer, K.; Gaddy, C.D.; Seaver, D.A.; Stillwell, W.G.
1985-01-01
The US Nuclear Regulatory Commission and Sandia National Laboratories sponsored a project to evaluate psychological scaling techniques for use in generating estimates of human error probabilities. The project evaluated two techniques: direct numerical estimation and paired comparisons. Expert estimates were found to be consistent across and within judges. Convergent validity was good, in comparison to estimates in a handbook of human reliability. Predictive validity could not be established because of the lack of actual relative frequencies of error (which will be a difficulty inherent in validation of any procedure used to estimate HEPs). Application of expert estimates in probabilistic risk assessment and in human factors is discussed
International Nuclear Information System (INIS)
Stillwell, W.G.; Seaver, D.A.; Schwartz, J.P.
1982-05-01
This report reviews probability assessment and psychological scaling techniques that could be used to estimate human error probabilities (HEPs) in nuclear power plant operations. The techniques rely on expert opinion and can be used to estimate HEPs where data do not exist or are inadequate. These techniques have been used in various other contexts and have been shown to produce reasonably accurate probabilities. Some problems do exist, and limitations are discussed. Additional topics covered include methods for combining estimates from multiple experts, the effects of training on probability estimates, and some ideas on structuring the relationship between performance shaping factors and HEPs. Preliminary recommendations are provided along with cautions regarding the costs of implementing the recommendations. Additional research is required before definitive recommendations can be made
Demonstration Integrated Knowledge-Based System for Estimating Human Error Probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, Jack L.
1999-04-21
Human Reliability Analysis (HRA) is currently comprised of at least 40 different methods that are used to analyze, predict, and evaluate human performance in probabilistic terms. Systematic HRAs allow analysts to examine human-machine relationships, identify error-likely situations, and provide estimates of relative frequencies for human errors on critical tasks, highlighting the most beneficial areas for system improvements. Unfortunately, each of HRA's methods has a different philosophical approach, thereby producing estimates of human error probabilities (HEPs) that area better or worse match to the error likely situation of interest. Poor selection of methodology, or the improper application of techniques can produce invalid HEP estimates, where that erroneous estimation of potential human failure could have potentially severe consequences in terms of the estimated occurrence of injury, death, and/or property damage.
International Nuclear Information System (INIS)
Seaver, D.A.; Stillwell, W.G.
1983-03-01
This report describes and evaluates several procedures for using expert judgment to estimate human-error probabilities (HEPs) in nuclear power plant operations. These HEPs are currently needed for several purposes, particularly for probabilistic risk assessments. Data do not exist for estimating these HEPs, so expert judgment can provide these estimates in a timely manner. Five judgmental procedures are described here: paired comparisons, ranking and rating, direct numerical estimation, indirect numerical estimation and multiattribute utility measurement. These procedures are evaluated in terms of several criteria: quality of judgments, difficulty of data collection, empirical support, acceptability, theoretical justification, and data processing. Situational constraints such as the number of experts available, the number of HEPs to be estimated, the time available, the location of the experts, and the resources available are discussed in regard to their implications for selecting a procedure for use
Energy Technology Data Exchange (ETDEWEB)
Jang, Seunghyun; Jae, Moosung [Hanyang University, Seoul (Korea, Republic of)
2016-10-15
The human failure events (HFEs) are considered in the development of system fault trees as well as accident sequence event trees in part of Probabilistic Safety Assessment (PSA). As a method for analyzing the human error, several methods, such as Technique for Human Error Rate Prediction (THERP), Human Cognitive Reliability (HCR), and Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) are used and new methods for human reliability analysis (HRA) are under developing at this time. This paper presents a dynamic HRA method for assessing the human failure events and estimation of human error probability for filtered containment venting system (FCVS) is performed. The action associated with implementation of the containment venting during a station blackout sequence is used as an example. In this report, dynamic HRA method was used to analyze FCVS-related operator action. The distributions of the required time and the available time were developed by MAAP code and LHS sampling. Though the numerical calculations given here are only for illustrative purpose, the dynamic HRA method can be useful tools to estimate the human error estimation and it can be applied to any kind of the operator actions, including the severe accident management strategy.
Quantitative estimation of the human error probability during soft control operations
International Nuclear Information System (INIS)
Lee, Seung Jun; Kim, Jaewhan; Jung, Wondea
2013-01-01
Highlights: ► An HRA method to evaluate execution HEP for soft control operations was proposed. ► The soft control tasks were analyzed and design-related influencing factors were identified. ► An application to evaluate the effects of soft controls was performed. - Abstract: In this work, a method was proposed for quantifying human errors that can occur during operation executions using soft controls. Soft controls of advanced main control rooms have totally different features from conventional controls, and thus they may have different human error modes and occurrence probabilities. It is important to identify the human error modes and quantify the error probability for evaluating the reliability of the system and preventing errors. This work suggests an evaluation framework for quantifying the execution error probability using soft controls. In the application result, it was observed that the human error probabilities of soft controls showed both positive and negative results compared to the conventional controls according to the design quality of advanced main control rooms
International Nuclear Information System (INIS)
Kim, Yochan; Park, Jinkyun; Jung, Wondea
2017-01-01
Because it has been indicated that empirical data supporting the estimates used in human reliability analysis (HRA) is insufficient, several databases have been constructed recently. To generate quantitative estimates from human reliability data, it is important to appropriately sort the erroneous behaviors found in the reliability data. Therefore, this paper proposes a scheme to classify the erroneous behaviors identified by the HuREX (Human Reliability data Extraction) framework through a review of the relevant literature. A case study of the human error probability (HEP) calculations is conducted to verify that the proposed scheme can be successfully implemented for the categorization of the erroneous behaviors and to assess whether the scheme is useful for the HEP quantification purposes. Although continuously accumulating and analyzing simulator data is desirable to secure more reliable HEPs, the resulting HEPs were insightful in several important ways with regard to human reliability in off-normal conditions. From the findings of the literature review and the case study, the potential and limitations of the proposed method are discussed. - Highlights: • A taxonomy of erroneous behaviors is proposed to estimate HEPs from a database. • The cognitive models, procedures, HRA methods, and HRA databases were reviewed. • HEPs for several types of erroneous behaviors are calculated as a case study.
Estimation of the human error probabilities in the human reliability analysis
International Nuclear Information System (INIS)
Liu Haibin; He Xuhong; Tong Jiejuan; Shen Shifei
2006-01-01
Human error data is an important issue of human reliability analysis (HRA). Using of Bayesian parameter estimation, which can use multiple information, such as the historical data of NPP and expert judgment data to modify the human error data, could get the human error data reflecting the real situation of NPP more truly. This paper, using the numeric compute program developed by the authors, presents some typical examples to illustrate the process of the Bayesian parameter estimation in HRA and discusses the effect of different modification data on the Bayesian parameter estimation. (authors)
International Nuclear Information System (INIS)
Nascimento, C.S. do; Mesquita, R.N. de
2009-01-01
Recent studies point human error as an important factor for many industrial and nuclear accidents: Three Mile Island (1979), Bhopal (1984), Chernobyl and Challenger (1986) are classical examples. Human contribution to these accidents may be better understood and analyzed by using Human Reliability Analysis (HRA), which has being taken as an essential part on Probabilistic Safety Analysis (PSA) of nuclear plants. Both HRA and PSA depend on Human Error Probability (HEP) for a quantitative analysis. These probabilities are extremely affected by the Performance Shaping Factors (PSF), which has a direct effect on human behavior and thus shape HEP according with specific environment conditions and personal individual characteristics which are responsible for these actions. This PSF dependence raises a great problem on data availability as turn these scarcely existent database too much generic or too much specific. Besides this, most of nuclear plants do not keep historical records of human error occurrences. Therefore, in order to overcome this occasional data shortage, a methodology based on Fuzzy Inference and expert judgment was employed in this paper in order to determine human error occurrence probabilities and to evaluate PSF's on performed actions by operators in a nuclear power plant (IEA-R1 nuclear reactor). Obtained HEP values were compared with reference tabled data used on current literature in order to show method coherence and valid approach. This comparison leads to a conclusion that this work results are able to be employed both on HRA and PSA enabling efficient prospection of plant safety conditions, operational procedures and local working conditions potential improvements (author)
International Nuclear Information System (INIS)
Kim, Yochan; Park, Jinkyun; Jung, Wondea; Jang, Inseok; Hyun Seong, Poong
2015-01-01
Despite recent efforts toward data collection for supporting human reliability analysis, there remains a lack of empirical basis in determining the effects of performance shaping factors (PSFs) on human error probabilities (HEPs). To enhance the empirical basis regarding the effects of the PSFs, a statistical methodology using a logistic regression and stepwise variable selection was proposed, and the effects of the PSF on HEPs related with the soft controls were estimated through the methodology. For this estimation, more than 600 human error opportunities related to soft controls in a computerized control room were obtained through laboratory experiments. From the eight PSF surrogates and combinations of these variables, the procedure quality, practice level, and the operation type were identified as significant factors for screen switch and mode conversion errors. The contributions of these significant factors to HEPs were also estimated in terms of a multiplicative form. The usefulness and limitation of the experimental data and the techniques employed are discussed herein, and we believe that the logistic regression and stepwise variable selection methods will provide a way to estimate the effects of PSFs on HEPs in an objective manner. - Highlights: • It is necessary to develop an empirical basis for the effects of the PSFs on the HEPs. • A statistical method using a logistic regression and variable selection was proposed. • The effects of PSFs on the HEPs of soft controls were empirically investigated. • The significant factors were identified and their effects were estimated
Estimating Subjective Probabilities
DEFF Research Database (Denmark)
Andersen, Steffen; Fountain, John; Harrison, Glenn W.
2014-01-01
either construct elicitation mechanisms that control for risk aversion, or construct elicitation mechanisms which undertake 'calibrating adjustments' to elicited reports. We illustrate how the joint estimation of risk attitudes and subjective probabilities can provide the calibration adjustments...... that theory calls for. We illustrate this approach using data from a controlled experiment with real monetary consequences to the subjects. This allows the observer to make inferences about the latent subjective probability, under virtually any well-specified model of choice under subjective risk, while still...
Dependent Human Error Probability Assessment
International Nuclear Information System (INIS)
Simic, Z.; Mikulicic, V.; Vukovic, I.
2006-01-01
This paper presents an assessment of the dependence between dynamic operator actions modeled in a Nuclear Power Plant (NPP) PRA and estimate the associated impact on Core damage frequency (CDF). This assessment was done improve HEP dependencies implementation inside existing PRA. All of the dynamic operator actions modeled in the NPP PRA are included in this assessment. Determining the level of HEP dependence and the associated influence on CDF are the major steps of this assessment. A decision on how to apply the results, i.e., should permanent HEP model changes be made, is based on the resulting relative CDF increase. Some CDF increase was selected as a threshold based on the NPP base CDF value and acceptance guidelines from the Regulatory Guide 1.174. HEP dependence resulting in a CDF increase of > 5E-07 would be considered potential candidates for specific incorporation into the baseline model. The approach used to judge the level of dependence between operator actions is based on dependency level categories and conditional probabilities developed in the Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications NUREG/CR-1278. To simplify the process, NUREG/CR-1278 identifies five levels of dependence: ZD (zero dependence), LD (low dependence), MD (moderate dependence), HD (high dependence), and CD (complete dependence). NUREG/CR-1278 also identifies several qualitative factors that could be involved in determining the level of dependence. Based on the NUREG/CR-1278 information, Time, Function, and Spatial attributes were judged to be the most important considerations when determining the level of dependence between operator actions within an accident sequence. These attributes were used to develop qualitative criteria (rules) that were used to judge the level of dependence (CD, HD, MD, LD, ZD) between the operator actions. After the level of dependence between the various HEPs is judged, quantitative values associated with the
Ben Issaid, Chaouki; Park, Kihong; Alouini, Mohamed-Slim
2017-01-01
When assessing the performance of the free space optical (FSO) communication systems, the outage probability encountered is generally very small, and thereby the use of nave Monte Carlo simulations becomes prohibitively expensive. To estimate these rare event probabilities, we propose in this work an importance sampling approach which is based on the exponential twisting technique to offer fast and accurate results. In fact, we consider a variety of turbulence regimes, and we investigate the outage probability of FSO communication systems, under a generalized pointing error model based on the Beckmann distribution, for both single and multihop scenarios. Selected numerical simulations are presented to show the accuracy and the efficiency of our approach compared to naive Monte Carlo.
Ben Issaid, Chaouki
2017-07-28
When assessing the performance of the free space optical (FSO) communication systems, the outage probability encountered is generally very small, and thereby the use of nave Monte Carlo simulations becomes prohibitively expensive. To estimate these rare event probabilities, we propose in this work an importance sampling approach which is based on the exponential twisting technique to offer fast and accurate results. In fact, we consider a variety of turbulence regimes, and we investigate the outage probability of FSO communication systems, under a generalized pointing error model based on the Beckmann distribution, for both single and multihop scenarios. Selected numerical simulations are presented to show the accuracy and the efficiency of our approach compared to naive Monte Carlo.
Collection of offshore human error probability data
International Nuclear Information System (INIS)
Basra, Gurpreet; Kirwan, Barry
1998-01-01
Accidents such as Piper Alpha have increased concern about the effects of human errors in complex systems. Such accidents can in theory be predicted and prevented by risk assessment, and in particular human reliability assessment (HRA), but HRA ideally requires qualitative and quantitative human error data. A research initiative at the University of Birmingham led to the development of CORE-DATA, a Computerised Human Error Data Base. This system currently contains a reasonably large number of human error data points, collected from a variety of mainly nuclear-power related sources. This article outlines a recent offshore data collection study, concerned with collecting lifeboat evacuation data. Data collection methods are outlined and a selection of human error probabilities generated as a result of the study are provided. These data give insights into the type of errors and human failure rates that could be utilised to support offshore risk analyses
Error probabilities in default Bayesian hypothesis testing
Gu, Xin; Hoijtink, Herbert; Mulder, J,
2016-01-01
This paper investigates the classical type I and type II error probabilities of default Bayes factors for a Bayesian t test. Default Bayes factors quantify the relative evidence between the null hypothesis and the unrestricted alternative hypothesis without needing to specify prior distributions for
Simulator data on human error probabilities
International Nuclear Information System (INIS)
Kozinsky, E.J.; Guttmann, H.E.
1982-01-01
Analysis of operator errors on NPP simulators is being used to determine Human Error Probabilities (HEP) for task elements defined in NUREG/CR 1278. Simulator data tapes from research conducted by EPRI and ORNL are being analyzed for operator error rates. The tapes collected, using Performance Measurement System software developed for EPRI, contain a history of all operator manipulations during simulated casualties. Analysis yields a time history or Operational Sequence Diagram and a manipulation summary, both stored in computer data files. Data searches yield information on operator errors of omission and commission. This work experimentally determines HEPs for Probabilistic Risk Assessment calculations. It is the only practical experimental source of this data to date
Simulator data on human error probabilities
International Nuclear Information System (INIS)
Kozinsky, E.J.; Guttmann, H.E.
1981-01-01
Analysis of operator errors on NPP simulators is being used to determine Human Error Probabilities (HEP) for task elements defined in NUREG/CR-1278. Simulator data tapes from research conducted by EPRI and ORNL are being analyzed for operator error rates. The tapes collected, using Performance Measurement System software developed for EPRI, contain a history of all operator manipulations during simulated casualties. Analysis yields a time history or Operational Sequence Diagram and a manipulation summary, both stored in computer data files. Data searches yield information on operator errors of omission and commission. This work experimentally determined HEP's for Probabilistic Risk Assessment calculations. It is the only practical experimental source of this data to date
The probability and the management of human error
International Nuclear Information System (INIS)
Dufey, R.B.; Saull, J.W.
2004-01-01
Embedded within modern technological systems, human error is the largest, and indeed dominant contributor to accident cause. The consequences dominate the risk profiles for nuclear power and for many other technologies. We need to quantify the probability of human error for the system as an integral contribution within the overall system failure, as it is generally not separable or predictable for actual events. We also need to provide a means to manage and effectively reduce the failure (error) rate. The fact that humans learn from their mistakes allows a new determination of the dynamic probability and human failure (error) rate in technological systems. The result is consistent with and derived from the available world data for modern technological systems. Comparisons are made to actual data from large technological systems and recent catastrophes. Best estimate values and relationships can be derived for both the human error rate, and for the probability. We describe the potential for new approaches to the management of human error and safety indicators, based on the principles of error state exclusion and of the systematic effect of learning. A new equation is given for the probability of human error (λ) that combines the influences of early inexperience, learning from experience (ε) and stochastic occurrences with having a finite minimum rate, this equation is λ 5.10 -5 + ((1/ε) - 5.10 -5 ) exp(-3*ε). The future failure rate is entirely determined by the experience: thus the past defines the future
Human Error Probability Assessment During Maintenance Activities of Marine Systems
Directory of Open Access Journals (Sweden)
Rabiul Islam
2018-03-01
Full Text Available Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man–machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue or external (i.e., environmental and operational conditions
Risk estimation using probability machines
2014-01-01
Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306
International Nuclear Information System (INIS)
Wilson, Brandon M; Smith, Barton L
2013-01-01
Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)
Wind power error estimation in resource assessments.
Directory of Open Access Journals (Sweden)
Osvaldo Rodríguez
Full Text Available Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.
Wind power error estimation in resource assessments.
Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel
2015-01-01
Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.
Probability shapes perceptual precision: A study in orientation estimation.
Jabar, Syaheed B; Anderson, Britt
2015-12-01
Probability is known to affect perceptual estimations, but an understanding of mechanisms is lacking. Moving beyond binary classification tasks, we had naive participants report the orientation of briefly viewed gratings where we systematically manipulated contingent probability. Participants rapidly developed faster and more precise estimations for high-probability tilts. The shapes of their error distributions, as indexed by a kurtosis measure, also showed a distortion from Gaussian. This kurtosis metric was robust, capturing probability effects that were graded, contextual, and varying as a function of stimulus orientation. Our data can be understood as a probability-induced reduction in the variability or "shape" of estimation errors, as would be expected if probability affects the perceptual representations. As probability manipulations are an implicit component of many endogenous cuing paradigms, changes at the perceptual level could account for changes in performance that might have traditionally been ascribed to "attention." (c) 2015 APA, all rights reserved).
Quantification of the effects of dependence on human error probabilities
International Nuclear Information System (INIS)
Bell, B.J.; Swain, A.D.
1980-01-01
In estimating the probabilities of human error in the performance of a series of tasks in a nuclear power plant, the situation-specific characteristics of the series must be considered. A critical factor not to be overlooked in this estimation is the dependence or independence that pertains to any of the several pairs of task performances. In discussing the quantification of the effects of dependence, the event tree symbology described will be used. In any series of tasks, the only dependence considered for quantification in this document will be that existing between the task of interest and the immediately preceeding task. Tasks performed earlier in the series may have some effect on the end task, but this effect is considered negligible
Human error probability quantification using fuzzy methodology in nuclear plants
International Nuclear Information System (INIS)
Nascimento, Claudio Souza do
2010-01-01
This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)
Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines
Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.
2011-01-01
Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433
A Quantum Theoretical Explanation for Probability Judgment Errors
Busemeyer, Jerome R.; Pothos, Emmanuel M.; Franco, Riccardo; Trueblood, Jennifer S.
2011-01-01
A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector…
Huo, Ming-Xia; Li, Ying
2017-12-01
Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.
Impact of controlling the sum of error probability in the sequential probability ratio test
Directory of Open Access Journals (Sweden)
Bijoy Kumarr Pradhan
2013-05-01
Full Text Available A generalized modified method is proposed to control the sum of error probabilities in sequential probability ratio test to minimize the weighted average of the two average sample numbers under a simple null hypothesis and a simple alternative hypothesis with the restriction that the sum of error probabilities is a pre-assigned constant to find the optimal sample size and finally a comparison is done with the optimal sample size found from fixed sample size procedure. The results are applied to the cases when the random variate follows a normal law as well as Bernoullian law.
Optimizing Probability of Detection Point Estimate Demonstration
Koshti, Ajay M.
2017-01-01
Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.
Modelling soft error probability in firmware: A case study
African Journals Online (AJOL)
The purpose is to estimate the probability that external disruptive events (such as ..... also changed the 16-bit magic variable to its unique 'magic' value. .... is mutually independent, not only over registers but over spikes, such that the above.
High throughput nonparametric probability density estimation.
Farmer, Jenny; Jacobs, Donald
2018-01-01
In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.
Clock error models for simulation and estimation
International Nuclear Information System (INIS)
Meditch, J.S.
1981-10-01
Mathematical models for the simulation and estimation of errors in precision oscillators used as time references in satellite navigation systems are developed. The results, based on all currently known oscillator error sources, are directly implementable on a digital computer. The simulation formulation is sufficiently flexible to allow for the inclusion or exclusion of individual error sources as desired. The estimation algorithms, following from Kalman filter theory, provide directly for the error analysis of clock errors in both filtering and prediction
ERF/ERFC, Calculation of Error Function, Complementary Error Function, Probability Integrals
International Nuclear Information System (INIS)
Vogel, J.E.
1983-01-01
1 - Description of problem or function: ERF and ERFC are used to compute values of the error function and complementary error function for any real number. They may be used to compute other related functions such as the normal probability integrals. 4. Method of solution: The error function and complementary error function are approximated by rational functions. Three such rational approximations are used depending on whether - x .GE.4.0. In the first region the error function is computed directly and the complementary error function is computed via the identity erfc(x)=1.0-erf(x). In the other two regions the complementary error function is computed directly and the error function is computed from the identity erf(x)=1.0-erfc(x). The error function and complementary error function are real-valued functions of any real argument. The range of the error function is (-1,1). The range of the complementary error function is (0,2). 5. Restrictions on the complexity of the problem: The user is cautioned against using ERF to compute the complementary error function by using the identity erfc(x)=1.0-erf(x). This subtraction may cause partial or total loss of significance for certain values of x
Closed Form Aliasing Probability For Q-ary Symmetric Errors
Directory of Open Access Journals (Sweden)
Geetani Edirisooriya
1996-01-01
Full Text Available In Built-In Self-Test (BIST techniques, test data reduction can be achieved using Linear Feedback Shift Registers (LFSRs. A faulty circuit may escape detection due to loss of information inherent to data compaction schemes. This is referred to as aliasing. The probability of aliasing in Multiple-Input Shift-Registers (MISRs has been studied under various bit error models. By modeling the signature analyzer as a Markov process we show that the closed form expression derived for aliasing probability previously, for MISRs with primitive polynomials under q-ary symmetric error model holds for all MISRs irrespective of their feedback polynomials and for group cellular automata signature analyzers as well. If the erroneous behaviour of a circuit can be modelled with q-ary symmetric errors, then the test circuit complexity and propagation delay associated with the signature analyzer can be minimized by using a set of m single bit LFSRs without increasing the probability of aliasing.
Risk Probability Estimating Based on Clustering
DEFF Research Database (Denmark)
Chen, Yong; Jensen, Christian D.; Gray, Elizabeth
2003-01-01
of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...
Error Covariance Estimation of Mesoscale Data Assimilation
National Research Council Canada - National Science Library
Xu, Qin
2005-01-01
The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...
Bayesian estimation of core-melt probability
International Nuclear Information System (INIS)
Lewis, H.W.
1984-01-01
A very simple application of the canonical Bayesian algorithm is made to the problem of estimation of the probability of core melt in a commercial power reactor. An approximation to the results of the Rasmussen study on reactor safety is used as the prior distribution, and the observation that there has been no core melt yet is used as the single experiment. The result is a substantial decrease in the mean probability of core melt--factors of 2 to 4 for reasonable choices of parameters. The purpose is to illustrate the procedure, not to argue for the decrease
Error Probability Analysis of Hardware Impaired Systems with Asymmetric Transmission
Javed, Sidrah; Amin, Osama; Ikki, Salama S.; Alouini, Mohamed-Slim
2018-01-01
Error probability study of the hardware impaired (HWI) systems highly depends on the adopted model. Recent models have proved that the aggregate noise is equivalent to improper Gaussian signals. Therefore, considering the distinct noise nature and self-interfering (SI) signals, an optimal maximum likelihood (ML) receiver is derived. This renders the conventional minimum Euclidean distance (MED) receiver as a sub-optimal receiver because it is based on the assumptions of ideal hardware transceivers and proper Gaussian noise in communication systems. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds and approximations are derived for various adopted systems including transmitter and receiver I/Q imbalanced systems with or without transmitter distortions as well as transmitter or receiver only impaired systems. Motivated by recent studies that shed the light on the benefit of improper Gaussian signaling in mitigating the HWIs, asymmetric quadrature amplitude modulation or phase shift keying is optimized and adapted for transmission. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver, the tightness of the derived bounds and effectiveness of asymmetric transmission in dampening HWIs and improving overall system performance
Error Probability Analysis of Hardware Impaired Systems with Asymmetric Transmission
Javed, Sidrah
2018-04-26
Error probability study of the hardware impaired (HWI) systems highly depends on the adopted model. Recent models have proved that the aggregate noise is equivalent to improper Gaussian signals. Therefore, considering the distinct noise nature and self-interfering (SI) signals, an optimal maximum likelihood (ML) receiver is derived. This renders the conventional minimum Euclidean distance (MED) receiver as a sub-optimal receiver because it is based on the assumptions of ideal hardware transceivers and proper Gaussian noise in communication systems. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds and approximations are derived for various adopted systems including transmitter and receiver I/Q imbalanced systems with or without transmitter distortions as well as transmitter or receiver only impaired systems. Motivated by recent studies that shed the light on the benefit of improper Gaussian signaling in mitigating the HWIs, asymmetric quadrature amplitude modulation or phase shift keying is optimized and adapted for transmission. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver, the tightness of the derived bounds and effectiveness of asymmetric transmission in dampening HWIs and improving overall system performance
A framework to assess diagnosis error probabilities in the advanced MCR
Energy Technology Data Exchange (ETDEWEB)
Kim, Ar Ryum; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of); Kim, Jong Hyun [Chosun University, Gwangju (Korea, Republic of); Jang, Inseok; Park, Jinkyun [Korea Atomic Research Institute, Daejeon (Korea, Republic of)
2016-10-15
The Institute of Nuclear Power Operations (INPO)’s operating experience database revealed that about 48% of the total events in world NPPs for 2 years (2010-2011) happened due to human errors. The purposes of human reliability analysis (HRA) method are to evaluate the potential for, and mechanism of, human errors that may affect plant safety. Accordingly, various HRA methods have been developed such as technique for human error rate prediction (THERP), simplified plant analysis risk human reliability assessment (SPAR-H), cognitive reliability and error analysis method (CREAM) and so on. Many researchers have asserted that procedure, alarm, and display are critical factors to affect operators’ generic activities, especially for diagnosis activities. None of various HRA methods was explicitly designed to deal with digital systems. SCHEME (Soft Control Human error Evaluation MEthod) considers only for the probability of soft control execution error in the advanced MCR. The necessity of developing HRA methods in various conditions of NPPs has been raised. In this research, the framework to estimate diagnosis error probabilities in the advanced MCR was suggested. The assessment framework was suggested by three steps. The first step is to investigate diagnosis errors and calculate their probabilities. The second step is to quantitatively estimate PSFs’ weightings in the advanced MCR. The third step is to suggest the updated TRC model to assess the nominal diagnosis error probabilities. Additionally, the proposed framework was applied by using the full-scope simulation. Experiments conducted in domestic full-scope simulator and HAMMLAB were used as data-source. Total eighteen tasks were analyzed and twenty-three crews participated in.
Statistical errors in Monte Carlo estimates of systematic errors
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k2. The specific terms unisim and multisim were coined by Peter Meyers and Steve Brice, respectively, for the MiniBooNE experiment. However, the concepts have been developed over time and have been in general use for some time.
Statistical errors in Monte Carlo estimates of systematic errors
Energy Technology Data Exchange (ETDEWEB)
Roe, Byron P. [Department of Physics, University of Michigan, Ann Arbor, MI 48109 (United States)]. E-mail: byronroe@umich.edu
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k{sup 2}.
Statistical errors in Monte Carlo estimates of systematic errors
International Nuclear Information System (INIS)
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k 2
Bayesian ensemble approach to error estimation of interatomic potentials
DEFF Research Database (Denmark)
Frederiksen, Søren Lund; Jacobsen, Karsten Wedel; Brown, K.S.
2004-01-01
Using a Bayesian approach a general method is developed to assess error bars on predictions made by models fitted to data. The error bars are estimated from fluctuations in ensembles of models sampling the model-parameter space with a probability density set by the minimum cost. The method...... is applied to the development of interatomic potentials for molybdenum using various potential forms and databases based on atomic forces. The calculated error bars on elastic constants, gamma-surface energies, structural energies, and dislocation properties are shown to provide realistic estimates...
Error estimation and adaptivity for incompressible hyperelasticity
Whiteley, J.P.
2014-04-30
SUMMARY: A Galerkin FEM is developed for nonlinear, incompressible (hyper) elasticity that takes account of nonlinearities in both the strain tensor and the relationship between the strain tensor and the stress tensor. By using suitably defined linearised dual problems with appropriate boundary conditions, a posteriori error estimates are then derived for both linear functionals of the solution and linear functionals of the stress on a boundary, where Dirichlet boundary conditions are applied. A second, higher order method for calculating a linear functional of the stress on a Dirichlet boundary is also presented together with an a posteriori error estimator for this approach. An implementation for a 2D model problem with known solution, where the entries of the strain tensor exhibit large, rapid variations, demonstrates the accuracy and sharpness of the error estimators. Finally, using a selection of model problems, the a posteriori error estimate is shown to provide a basis for effective mesh adaptivity. © 2014 John Wiley & Sons, Ltd.
Probable sources of errors in radiation therapy (abstract)
International Nuclear Information System (INIS)
Khan, U.H.
1998-01-01
It is fact that some errors are always in dose-volume prescription, management of radiation beam, derivation of exposure, planning the treatment and finally the treatment of the patient ( a three dimensional subject). This paper highlights all the sources of error and relevant methods to decrease or eliminate them, thus improving the over-all therapeutic efficiency and accuracy. It is a comprehensive teamwork of the radiotherapist, medical radiation physicist, medical technologist and the patient. All the links, in the whole chain of radiotherapy, are equally important and duly considered in the paper. The decision for Palliative or Radical treatment is based on the nature and extent disease, site, stage, grade, length of the history of condition and biopsy reports etc. This may entail certain uncertainties in Volume of tumor, quality and quantity of radiation and dose fractionation etc, which may be under or over-estimated. An effort has been made to guide the radiotherapist in avoiding the pitfalls in the arena of radiotherapy. (author)
Comparison of density estimators. [Estimation of probability density functions
Energy Technology Data Exchange (ETDEWEB)
Kao, S.; Monahan, J.F.
1977-09-01
Recent work in the field of probability density estimation has included the introduction of some new methods, such as the polynomial and spline methods and the nearest neighbor method, and the study of asymptotic properties in depth. This earlier work is summarized here. In addition, the computational complexity of the various algorithms is analyzed, as are some simulations. The object is to compare the performance of the various methods in small samples and their sensitivity to change in their parameters, and to attempt to discover at what point a sample is so small that density estimation can no longer be worthwhile. (RWR)
Estimation of the probability of success in petroleum exploration
Davis, J.C.
1977-01-01
A probabilistic model for oil exploration can be developed by assessing the conditional relationship between perceived geologic variables and the subsequent discovery of petroleum. Such a model includes two probabilistic components, the first reflecting the association between a geologic condition (structural closure, for example) and the occurrence of oil, and the second reflecting the uncertainty associated with the estimation of geologic variables in areas of limited control. Estimates of the conditional relationship between geologic variables and subsequent production can be found by analyzing the exploration history of a "training area" judged to be geologically similar to the exploration area. The geologic variables are assessed over the training area using an historical subset of the available data, whose density corresponds to the present control density in the exploration area. The success or failure of wells drilled in the training area subsequent to the time corresponding to the historical subset provides empirical estimates of the probability of success conditional upon geology. Uncertainty in perception of geological conditions may be estimated from the distribution of errors made in geologic assessment using the historical subset of control wells. These errors may be expressed as a linear function of distance from available control. Alternatively, the uncertainty may be found by calculating the semivariogram of the geologic variables used in the analysis: the two procedures will yield approximately equivalent results. The empirical probability functions may then be transferred to the exploration area and used to estimate the likelihood of success of specific exploration plays. These estimates will reflect both the conditional relationship between the geological variables used to guide exploration and the uncertainty resulting from lack of control. The technique is illustrated with case histories from the mid-Continent area of the U.S.A. ?? 1977 Plenum
Error estimation in plant growth analysis
Directory of Open Access Journals (Sweden)
Andrzej Gregorczyk
2014-01-01
Full Text Available The scheme is presented for calculation of errors of dry matter values which occur during approximation of data with growth curves, determined by the analytical method (logistic function and by the numerical method (Richards function. Further formulae are shown, which describe absolute errors of growth characteristics: Growth rate (GR, Relative growth rate (RGR, Unit leaf rate (ULR and Leaf area ratio (LAR. Calculation examples concerning the growth course of oats and maize plants are given. The critical analysis of the estimation of obtained results has been done. The purposefulness of joint application of statistical methods and error calculus in plant growth analysis has been ascertained.
KMRR thermal power measurement error estimation
International Nuclear Information System (INIS)
Rhee, B.W.; Sim, B.S.; Lim, I.C.; Oh, S.K.
1990-01-01
The thermal power measurement error of the Korea Multi-purpose Research Reactor has been estimated by a statistical Monte Carlo method, and compared with those obtained by the other methods including deterministic and statistical approaches. The results show that the specified thermal power measurement error of 5% cannot be achieved if the commercial RTDs are used to measure the coolant temperatures of the secondary cooling system and the error can be reduced below the requirement if the commercial RTDs are replaced by the precision RTDs. The possible range of the thermal power control operation has been identified to be from 100% to 20% of full power
Basic considerations in predicting error probabilities in human task performance
International Nuclear Information System (INIS)
Fleishman, E.A.; Buffardi, L.C.; Allen, J.A.; Gaskins, R.C. III
1990-04-01
It is well established that human error plays a major role in the malfunctioning of complex systems. This report takes a broad look at the study of human error and addresses the conceptual, methodological, and measurement issues involved in defining and describing errors in complex systems. In addition, a review of existing sources of human reliability data and approaches to human performance data base development is presented. Alternative task taxonomies, which are promising for establishing the comparability on nuclear and non-nuclear tasks, are also identified. Based on such taxonomic schemes, various data base prototypes for generalizing human error rates across settings are proposed. 60 refs., 3 figs., 7 tabs
The relative impact of sizing errors on steam generator tube failure probability
International Nuclear Information System (INIS)
Cizelj, L.; Dvorsek, T.
1998-01-01
The Outside Diameter Stress Corrosion Cracking (ODSCC) at tube support plates is currently the major degradation mechanism affecting the steam generator tubes made of Inconel 600. This caused development and licensing of degradation specific maintenance approaches, which addressed two main failure modes of the degraded piping: tube rupture; and excessive leakage through degraded tubes. A methodology aiming at assessing the efficiency of a given set of possible maintenance approaches has already been proposed by the authors. It pointed out better performance of the degradation specific over generic approaches in (1) lower probability of single and multiple steam generator tube rupture (SGTR), (2) lower estimated accidental leak rates and (3) less tubes plugged. A sensitivity analysis was also performed pointing out the relative contributions of uncertain input parameters to the tube rupture probabilities. The dominant contribution was assigned to the uncertainties inherent to the regression models used to correlate the defect size and tube burst pressure. The uncertainties, which can be estimated from the in-service inspections, are further analysed in this paper. The defect growth was found to have significant and to some extent unrealistic impact on the probability of single tube rupture. Since the defect growth estimates were based on the past inspection records they strongly depend on the sizing errors. Therefore, an attempt was made to filter out the sizing errors and to arrive at more realistic estimates of the defect growth. The impact of different assumptions regarding sizing errors on the tube rupture probability was studied using a realistic numerical example. The data used is obtained from a series of inspection results from Krsko NPP with 2 Westinghouse D-4 steam generators. The results obtained are considered useful in safety assessment and maintenance of affected steam generators. (author)
A posteriori error estimates in voice source recovery
Leonov, A. S.; Sorokin, V. N.
2017-12-01
The inverse problem of voice source pulse recovery from a segment of a speech signal is under consideration. A special mathematical model is used for the solution that relates these quantities. A variational method of solving inverse problem of voice source recovery for a new parametric class of sources, that is for piecewise-linear sources (PWL-sources), is proposed. Also, a technique for a posteriori numerical error estimation for obtained solutions is presented. A computer study of the adequacy of adopted speech production model with PWL-sources is performed in solving the inverse problems for various types of voice signals, as well as corresponding study of a posteriori error estimates. Numerical experiments for speech signals show satisfactory properties of proposed a posteriori error estimates, which represent the upper bounds of possible errors in solving the inverse problem. The estimate of the most probable error in determining the source-pulse shapes is about 7-8% for the investigated speech material. It is noted that a posteriori error estimates can be used as a criterion of the quality for obtained voice source pulses in application to speaker recognition.
The estimation of small probabilities and risk assessment
International Nuclear Information System (INIS)
Kalbfleisch, J.D.; Lawless, J.F.; MacKay, R.J.
1982-01-01
The primary contribution of statistics to risk assessment is in the estimation of probabilities. Frequently the probabilities in question are small, and their estimation is particularly difficult. The authors consider three examples illustrating some problems inherent in the estimation of small probabilities
Constrained motion estimation-based error resilient coding for HEVC
Guo, Weihan; Zhang, Yongfei; Li, Bo
2018-04-01
Unreliable communication channels might lead to packet losses and bit errors in the videos transmitted through it, which will cause severe video quality degradation. This is even worse for HEVC since more advanced and powerful motion estimation methods are introduced to further remove the inter-frame dependency and thus improve the coding efficiency. Once a Motion Vector (MV) is lost or corrupted, it will cause distortion in the decoded frame. More importantly, due to motion compensation, the error will propagate along the motion prediction path, accumulate over time, and significantly degrade the overall video presentation quality. To address this problem, we study the problem of encoder-sider error resilient coding for HEVC and propose a constrained motion estimation scheme to mitigate the problem of error propagation to subsequent frames. The approach is achieved by cutting off MV dependencies and limiting the block regions which are predicted by temporal motion vector. The experimental results show that the proposed method can effectively suppress the error propagation caused by bit errors of motion vector and can improve the robustness of the stream in the bit error channels. When the bit error probability is 10-5, an increase of the decoded video quality (PSNR) by up to1.310dB and on average 0.762 dB can be achieved, compared to the reference HEVC.
Massey, J. L.
1976-01-01
The very low error probability obtained with long error-correcting codes results in a very small number of observed errors in simulation studies of practical size and renders the usual confidence interval techniques inapplicable to the observed error probability. A natural extension of the notion of a 'confidence interval' is made and applied to such determinations of error probability by simulation. An example is included to show the surprisingly great significance of as few as two decoding errors in a very large number of decoding trials.
Estimating the Probability of Negative Events
Harris, Adam J. L.; Corner, Adam; Hahn, Ulrike
2009-01-01
How well we are attuned to the statistics of our environment is a fundamental question in understanding human behaviour. It seems particularly important to be able to provide accurate assessments of the probability with which negative events occur so as to guide rational choice of preventative actions. One question that arises here is whether or…
A precise error bound for quantum phase estimation.
Directory of Open Access Journals (Sweden)
James M Chappell
Full Text Available Quantum phase estimation is one of the key algorithms in the field of quantum computing, but up until now, only approximate expressions have been derived for the probability of error. We revisit these derivations, and find that by ensuring symmetry in the error definitions, an exact formula can be found. This new approach may also have value in solving other related problems in quantum computing, where an expected error is calculated. Expressions for two special cases of the formula are also developed, in the limit as the number of qubits in the quantum computer approaches infinity and in the limit as the extra added qubits to improve reliability goes to infinity. It is found that this formula is useful in validating computer simulations of the phase estimation procedure and in avoiding the overestimation of the number of qubits required in order to achieve a given reliability. This formula thus brings improved precision in the design of quantum computers.
Some aspects of statistical modeling of human-error probability
International Nuclear Information System (INIS)
Prairie, R.R.
1982-01-01
Human reliability analyses (HRA) are often performed as part of risk assessment and reliability projects. Recent events in nuclear power have shown the potential importance of the human element. There are several on-going efforts in the US and elsewhere with the purpose of modeling human error such that the human contribution can be incorporated into an overall risk assessment associated with one or more aspects of nuclear power. An effort that is described here uses the HRA (event tree) to quantify and model the human contribution to risk. As an example, risk analyses are being prepared on several nuclear power plants as part of the Interim Reliability Assessment Program (IREP). In this process the risk analyst selects the elements of his fault tree that could be contributed to by human error. He then solicits the HF analyst to do a HRA on this element
Human Error Probability Assessment During Maintenance Activities of Marine Systems
Rabiul Islam; Faisal Khan; Rouzbeh Abbassi; Vikram Garaniya
2018-01-01
Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man–machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personne...
Error estimation for variational nodal calculations
International Nuclear Information System (INIS)
Zhang, H.; Lewis, E.E.
1998-01-01
Adaptive grid methods are widely employed in finite element solutions to both solid and fluid mechanics problems. Either the size of the element is reduced (h refinement) or the order of the trial function is increased (p refinement) locally to improve the accuracy of the solution without a commensurate increase in computational effort. Success of these methods requires effective local error estimates to determine those parts of the problem domain where the solution should be refined. Adaptive methods have recently been applied to the spatial variables of the discrete ordinates equations. As a first step in the development of adaptive methods that are compatible with the variational nodal method, the authors examine error estimates for use in conjunction with spatial variables. The variational nodal method lends itself well to p refinement because the space-angle trial functions are hierarchical. Here they examine an error estimator for use with spatial p refinement for the diffusion approximation. Eventually, angular refinement will also be considered using spherical harmonics approximations
Probability of undetected error after decoding for a concatenated coding scheme
Costello, D. J., Jr.; Lin, S.
1984-01-01
A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for NASA telecommand system is analyzed.
Adaptive estimation of binomial probabilities under misclassification
Albers, Willem/Wim; Veldman, H.J.
1984-01-01
If misclassification occurs the standard binomial estimator is usually seriously biased. It is known that an improvement can be achieved by using more than one observer in classifying the sample elements. Here it will be investigated which number of observers is optimal given the total number of
Internal Medicine residents use heuristics to estimate disease probability
Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin
2015-01-01
Background: Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. Method: We randomized 55 In...
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
Directory of Open Access Journals (Sweden)
A. B. Levina
2016-03-01
Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking
Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.
Costello, Fintan; Watts, Paul
2018-01-01
We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.
Modeling and estimation of measurement errors
International Nuclear Information System (INIS)
Neuilly, M.
1998-01-01
Any person in charge of taking measures is aware of the inaccuracy of the results however cautiously he may handle. Sensibility, accuracy, reproducibility define the significance of a result. The use of statistical methods is one of the important tools to improve the quality of measurement. The accuracy due to these methods revealed the little difference in the isotopic composition of uranium ore which led to the discovery of Oklo fossil reactor. This book is dedicated to scientists and engineers interested in measurement whatever their investigation interests are. Experimental results are presented as random variables and their laws of probability are approximated by normal law, Poison law or Pearson distribution. The impact of 1 or more parameters on the total error can be evaluated by drawing factorial plans and by using variance analysis methods. This method is also used in intercomparison procedures between laboratories and to detect any abnormal shift in a series of measurement. (A.C.)
Quantification of type I error probabilities for heterogeneity LOD scores.
Abreu, Paula C; Hodge, Susan E; Greenberg, David A
2002-02-01
Locus heterogeneity is a major confounding factor in linkage analysis. When no prior knowledge of linkage exists, and one aims to detect linkage and heterogeneity simultaneously, classical distribution theory of log-likelihood ratios does not hold. Despite some theoretical work on this problem, no generally accepted practical guidelines exist. Nor has anyone rigorously examined the combined effect of testing for linkage and heterogeneity and simultaneously maximizing over two genetic models (dominant, recessive). The effect of linkage phase represents another uninvestigated issue. Using computer simulation, we investigated type I error (P value) of the "admixture" heterogeneity LOD (HLOD) score, i.e., the LOD score maximized over both recombination fraction theta and admixture parameter alpha and we compared this with the P values when one maximizes only with respect to theta (i.e., the standard LOD score). We generated datasets of phase-known and -unknown nuclear families, sizes k = 2, 4, and 6 children, under fully penetrant autosomal dominant inheritance. We analyzed these datasets (1) assuming a single genetic model, and maximizing the HLOD over theta and alpha; and (2) maximizing the HLOD additionally over two dominance models (dominant vs. recessive), then subtracting a 0.3 correction. For both (1) and (2), P values increased with family size k; rose less for phase-unknown families than for phase-known ones, with the former approaching the latter as k increased; and did not exceed the one-sided mixture distribution xi = (1/2) chi1(2) + (1/2) chi2(2). Thus, maximizing the HLOD over theta and alpha appears to add considerably less than an additional degree of freedom to the associated chi1(2) distribution. We conclude with practical guidelines for linkage investigators. Copyright 2002 Wiley-Liss, Inc.
Accounting Fraud: an estimation of detection probability
Directory of Open Access Journals (Sweden)
Artur Filipe Ewald Wuerges
2014-12-01
Full Text Available Financial statement fraud (FSF is costly for investors and can damage the credibility of the audit profession. To prevent and detect fraud, it is helpful to know its causes. The binary choice models (e.g. logit and probit commonly used in the extant literature, however, fail to account for undetected cases of fraud and thus present unreliable hypotheses tests. Using a sample of 118 companies accused of fraud by the Securities and Exchange Commission (SEC, we estimated a logit model that corrects the problems arising from undetected frauds in U.S. companies. To avoid multicollinearity problems, we extracted seven factors from 28 variables using the principal factors method. Our results indicate that only 1.43 percent of the instances of FSF were publicized by the SEC. Of the six significant variables included in the traditional, uncorrected logit model, three were found to be actually non-significant in the corrected model. The likelihood of FSF is 5.12 times higher when the firm’s auditor issues an adverse or qualified report.
Internal Medicine residents use heuristics to estimate disease probability
Directory of Open Access Journals (Sweden)
Sen Phang
2015-12-01
Conclusions: Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.
Extracting and Converting Quantitative Data into Human Error Probabilities
Energy Technology Data Exchange (ETDEWEB)
Tuan Q. Tran; Ronald L. Boring; Jeffrey C. Joe; Candice D. Griffith
2007-08-01
This paper discusses a proposed method using a combination of advanced statistical approaches (e.g., meta-analysis, regression, structural equation modeling) that will not only convert different empirical results into a common metric for scaling individual PSFs effects, but will also examine the complex interrelationships among PSFs. Furthermore, the paper discusses how the derived statistical estimates (i.e., effect sizes) can be mapped onto a HRA method (e.g. SPAR-H) to generate HEPs that can then be use in probabilistic risk assessment (PRA). The paper concludes with a discussion of the benefits of using academic literature in assisting HRA analysts in generating sound HEPs and HRA developers in validating current HRA models and formulating new HRA models.
Sporadic error probability due to alpha particles in dynamic memories of various technologies
International Nuclear Information System (INIS)
Edwards, D.G.
1980-01-01
The sensitivity of MOS memory components to errors induced by alpha particles is expected to increase with integration level. The soft error rate of a 65-kbit VMOS memory has been compared experimentally with that of three field-proven 16-kbit designs. The technological and design advantages of the VMOS RAM ensure an error rate which is lower than those of the 16-kbit memories. Calculation of the error probability for the 65-kbit RAM and comparison with the measurements show that for large duty cycles single particle hits lead to sensing errors and for small duty cycles cell errors caused by multiple hits predominate. (Auth.)
Estimating error rates for firearm evidence identifications in forensic science
Song, John; Vorburger, Theodore V.; Chu, Wei; Yen, James; Soons, Johannes A.; Ott, Daniel B.; Zhang, Nien Fan
2018-01-01
Estimating error rates for firearm evidence identification is a fundamental challenge in forensic science. This paper describes the recently developed congruent matching cells (CMC) method for image comparisons, its application to firearm evidence identification, and its usage and initial tests for error rate estimation. The CMC method divides compared topography images into correlation cells. Four identification parameters are defined for quantifying both the topography similarity of the correlated cell pairs and the pattern congruency of the registered cell locations. A declared match requires a significant number of CMCs, i.e., cell pairs that meet all similarity and congruency requirements. Initial testing on breech face impressions of a set of 40 cartridge cases fired with consecutively manufactured pistol slides showed wide separation between the distributions of CMC numbers observed for known matching and known non-matching image pairs. Another test on 95 cartridge cases from a different set of slides manufactured by the same process also yielded widely separated distributions. The test results were used to develop two statistical models for the probability mass function of CMC correlation scores. The models were applied to develop a framework for estimating cumulative false positive and false negative error rates and individual error rates of declared matches and non-matches for this population of breech face impressions. The prospect for applying the models to large populations and realistic case work is also discussed. The CMC method can provide a statistical foundation for estimating error rates in firearm evidence identifications, thus emulating methods used for forensic identification of DNA evidence. PMID:29331680
Two-step estimation in ratio-of-mediator-probability weighted causal mediation analysis.
Bein, Edward; Deutsch, Jonah; Hong, Guanglei; Porter, Kristin E; Qin, Xu; Yang, Cheng
2018-04-15
This study investigates appropriate estimation of estimator variability in the context of causal mediation analysis that employs propensity score-based weighting. Such an analysis decomposes the total effect of a treatment on the outcome into an indirect effect transmitted through a focal mediator and a direct effect bypassing the mediator. Ratio-of-mediator-probability weighting estimates these causal effects by adjusting for the confounding impact of a large number of pretreatment covariates through propensity score-based weighting. In step 1, a propensity score model is estimated. In step 2, the causal effects of interest are estimated using weights derived from the prior step's regression coefficient estimates. Statistical inferences obtained from this 2-step estimation procedure are potentially problematic if the estimated standard errors of the causal effect estimates do not reflect the sampling uncertainty in the estimation of the weights. This study extends to ratio-of-mediator-probability weighting analysis a solution to the 2-step estimation problem by stacking the score functions from both steps. We derive the asymptotic variance-covariance matrix for the indirect effect and direct effect 2-step estimators, provide simulation results, and illustrate with an application study. Our simulation results indicate that the sampling uncertainty in the estimated weights should not be ignored. The standard error estimation using the stacking procedure offers a viable alternative to bootstrap standard error estimation. We discuss broad implications of this approach for causal analysis involving propensity score-based weighting. Copyright © 2018 John Wiley & Sons, Ltd.
Basic human error probabilities in advanced MCRs when using soft control
International Nuclear Information System (INIS)
Jang, In Seok; Seong, Poong Hyun; Kang, Hyun Gook; Lee, Seung Jun
2012-01-01
In a report on one of the renowned HRA methods, Technique for Human Error Rate Prediction (THERP), it is pointed out that 'The paucity of actual data on human performance continues to be a major problem for estimating HEPs and performance times in nuclear power plant (NPP) task'. However, another critical difficulty is that most current HRA databases deal with operation in conventional type of MCRs. With the adoption of new human system interfaces that are based on computer based technologies, the operation environment of MCRs in NPPs has changed. The MCRs including these digital and computer technologies, such as large display panels, computerized procedures, soft controls, and so on, are called advanced MCRs. Because of the different interfaces, different Basic Human Error Probabilities (BHEPs) should be considered in human reliability analyses (HRAs) for advanced MCRs. This study carries out an empirical analysis of human error considering soft controls. The aim of this work is not only to compile a database using the simulator for advanced MCRs but also to compare BHEPs with those of a conventional MCR database
On the average capacity and bit error probability of wireless communication systems
Yilmaz, Ferkan; Alouini, Mohamed-Slim
2011-01-01
Analysis of the average binary error probabilities and average capacity of wireless communications systems over generalized fading channels have been considered separately in the past. This paper introduces a novel moment generating function
Radiation risk estimation based on measurement error models
Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya
2017-01-01
This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.
The estimation of collision probabilities in complicated geometries
International Nuclear Information System (INIS)
Roth, M.J.
1969-04-01
This paper demonstrates how collision probabilities in complicated geometries may be estimated. It is assumed that the reactor core may be divided into a number of cells each with simple geometry so that a collision probability matrix can be calculated for each cell by standard methods. It is then shown how these may be joined together. (author)
Estimated probability of the number of buildings damaged by the ...
African Journals Online (AJOL)
The analysis shows that the probability estimator of the building damage ... and homeowners) should reserve the cost of repair at least worth the risk of loss, to face ... Keywords: Citarum River; logistic regression; genetic algorithm; losses risk; ...
Crash probability estimation via quantifying driver hazard perception.
Li, Yang; Zheng, Yang; Wang, Jianqiang; Kodaka, Kenji; Li, Keqiang
2018-07-01
Crash probability estimation is an important method to predict the potential reduction of crash probability contributed by forward collision avoidance technologies (FCATs). In this study, we propose a practical approach to estimate crash probability, which combines a field operational test and numerical simulations of a typical rear-end crash model. To consider driver hazard perception characteristics, we define a novel hazard perception measure, called as driver risk response time, by considering both time-to-collision (TTC) and driver braking response to impending collision risk in a near-crash scenario. Also, we establish a driving database under mixed Chinese traffic conditions based on a CMBS (Collision Mitigation Braking Systems)-equipped vehicle. Applying the crash probability estimation in this database, we estimate the potential decrease in crash probability owing to use of CMBS. A comparison of the results with CMBS on and off shows a 13.7% reduction of crash probability in a typical rear-end near-crash scenario with a one-second delay of driver's braking response. These results indicate that CMBS is positive in collision prevention, especially in the case of inattentive drivers or ole drivers. The proposed crash probability estimation offers a practical way for evaluating the safety benefits in the design and testing of FCATs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Incorporation of various uncertainties in dependent failure-probability estimation
International Nuclear Information System (INIS)
Samanta, P.K.; Mitra, S.P.
1982-01-01
This paper describes an approach that allows the incorporation of various types of uncertainties in the estimation of dependent failure (common mode failure) probability. The types of uncertainties considered are attributable to data, modeling and coupling. The method developed is applied to a class of dependent failures, i.e., multiple human failures during testing, maintenance and calibration. Estimation of these failures is critical as they have been shown to be significant contributors to core melt probability in pressurized water reactors
Information-theoretic methods for estimating of complicated probability distributions
Zong, Zhi
2006-01-01
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur
Estimating market probabilities of future interest rate changes
Hlušek, Martin
2002-01-01
The goal of this paper is to estimate the market consensus forecast of future monetary policy development and to quantify the priced-in probability of interest rate changes for different future time horizons. The proposed model uses the current spot money market yield curve and available money market derivative instruments (forward rate agreements, FRAs) and estimates the market probability of interest rate changes up to a 12-month horizon.
Undetected error probability for data services in a terrestrial DAB single frequency network
Schiphorst, Roelof; Hoeksema, F.W.; Slump, Cornelis H.; Veldhuis, Raymond N.J.; Veldhuis, R.N.J.; Cronie, H.S.
2007-01-01
DAB (Digital Audio Broadcasting) is the European successor of FM radio. Besides audio services, other services such as traffic information can be provided. An important parameter for data services is the probability of non-recognized or undetected errors in the system. To derive this probability, we
Parts of the Whole: Error Estimation for Science Students
Directory of Open Access Journals (Sweden)
Dorothy Wallace
2017-01-01
Full Text Available It is important for science students to understand not only how to estimate error sizes in measurement data, but also to see how these errors contribute to errors in conclusions they may make about the data. Relatively small errors in measurement, errors in assumptions, and roundoff errors in computation may result in large error bounds on computed quantities of interest. In this column, we look closely at a standard method for measuring the volume of cancer tumor xenografts to see how small errors in each of these three factors may contribute to relatively large observed errors in recorded tumor volumes.
Calculating method on human error probabilities considering influence of management and organization
International Nuclear Information System (INIS)
Gao Jia; Huang Xiangrui; Shen Zupei
1996-01-01
This paper is concerned with how management and organizational influences can be factored into quantifying human error probabilities on risk assessments, using a three-level Influence Diagram (ID) which is originally only as a tool for construction and representation of models of decision-making trees or event trees. An analytical model of human errors causation has been set up with three influence levels, introducing a method for quantification assessments (of the ID), which can be applied into quantifying probabilities) of human errors on risk assessments, especially into the quantification of complex event trees (system) as engineering decision-making analysis. A numerical case study is provided to illustrate the approach
A Fast Soft Bit Error Rate Estimation Method
Directory of Open Access Journals (Sweden)
Ait-Idir Tarik
2010-01-01
Full Text Available We have suggested in a previous publication a method to estimate the Bit Error Rate (BER of a digital communications system instead of using the famous Monte Carlo (MC simulation. This method was based on the estimation of the probability density function (pdf of soft observed samples. The kernel method was used for the pdf estimation. In this paper, we suggest to use a Gaussian Mixture (GM model. The Expectation Maximisation algorithm is used to estimate the parameters of this mixture. The optimal number of Gaussians is computed by using Mutual Information Theory. The analytical expression of the BER is therefore simply given by using the different estimated parameters of the Gaussian Mixture. Simulation results are presented to compare the three mentioned methods: Monte Carlo, Kernel and Gaussian Mixture. We analyze the performance of the proposed BER estimator in the framework of a multiuser code division multiple access system and show that attractive performance is achieved compared with conventional MC or Kernel aided techniques. The results show that the GM method can drastically reduce the needed number of samples to estimate the BER in order to reduce the required simulation run-time, even at very low BER.
Detection probabilities for time-domain velocity estimation
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
1991-01-01
programs, it is demonstrated that the probability of correct estimation depends on the signal-to-noise ratio, transducer bandwidth, number of A-lines and number of samples used in the correlation estimate. The influence of applying a stationary echo-canceler is explained. The echo canceling can be modeled...
The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors
International Nuclear Information System (INIS)
Duffey, Romney B.; Saull, John W.
2006-01-01
Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the 'learning hypothesis' that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new 'best' equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world's commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum
Human error recovery failure probability when using soft controls in computerized control rooms
International Nuclear Information System (INIS)
Jang, Inseok; Kim, Ar Ryum; Seong, Poong Hyun; Jung, Wondea
2014-01-01
Many literatures categorized recovery process into three phases; detection of problem situation, explanation of problem causes or countermeasures against problem, and end of recovery. Although the focus of recovery promotion has been on categorizing recovery phases and modeling recovery process, research related to human recovery failure probabilities has not been perform actively. On the other hand, a few study regarding recovery failure probabilities were implemented empirically. Summarizing, researches that have performed so far have several problems in terms of use in human reliability analysis (HRA). By adopting new human-system interfaces that are based on computer-based technologies, the operation environment of MCRs in NPPs has changed from conventional MCRs to advanced MCRs. Because of the different interfaces between conventional and advanced MCRs, different recovery failure probabilities should be considered in the HRA for advanced MCRs. Therefore, this study carries out an empirical analysis of human error recovery probabilities under an advanced MCR mockup called compact nuclear simulator (CNS). The aim of this work is not only to compile a recovery failure probability database using the simulator for advanced MCRs but also to collect recovery failure probability according to defined human error modes to compare that which human error mode has highest recovery failure probability. The results show that recovery failure probability regarding wrong screen selection was lowest among human error modes, which means that most of human error related to wrong screen selection can be recovered. On the other hand, recovery failure probabilities of operation selection omission and delayed operation were 1.0. These results imply that once subject omitted one task in the procedure, they have difficulties finding and recovering their errors without supervisor's assistance. Also, wrong screen selection had an effect on delayed operation. That is, wrong screen
Effects of structural error on the estimates of parameters of dynamical systems
Hadaegh, F. Y.; Bekey, G. A.
1986-01-01
In this paper, the notion of 'near-equivalence in probability' is introduced for identifying a system in the presence of several error sources. Following some basic definitions, necessary and sufficient conditions for the identifiability of parameters are given. The effects of structural error on the parameter estimates for both the deterministic and stochastic cases are considered.
Estimation error algorithm at analysis of beta-spectra
International Nuclear Information System (INIS)
Bakovets, N.V.; Zhukovskij, A.I.; Zubarev, V.N.; Khadzhinov, E.M.
2005-01-01
This work describes the estimation error algorithm at the operations with beta-spectrums, as well as compares the theoretical and experimental errors by the processing of beta-channel's data. (authors)
Estimating the empirical probability of submarine landslide occurrence
Geist, Eric L.; Parsons, Thomas E.; Mosher, David C.; Shipp, Craig; Moscardelli, Lorena; Chaytor, Jason D.; Baxter, Christopher D. P.; Lee, Homa J.; Urgeles, Roger
2010-01-01
The empirical probability for the occurrence of submarine landslides at a given location can be estimated from age dates of past landslides. In this study, tools developed to estimate earthquake probability from paleoseismic horizons are adapted to estimate submarine landslide probability. In both types of estimates, one has to account for the uncertainty associated with age-dating individual events as well as the open time intervals before and after the observed sequence of landslides. For observed sequences of submarine landslides, we typically only have the age date of the youngest event and possibly of a seismic horizon that lies below the oldest event in a landslide sequence. We use an empirical Bayes analysis based on the Poisson-Gamma conjugate prior model specifically applied to the landslide probability problem. This model assumes that landslide events as imaged in geophysical data are independent and occur in time according to a Poisson distribution characterized by a rate parameter λ. With this method, we are able to estimate the most likely value of λ and, importantly, the range of uncertainty in this estimate. Examples considered include landslide sequences observed in the Santa Barbara Channel, California, and in Port Valdez, Alaska. We confirm that given the uncertainties of age dating that landslide complexes can be treated as single events by performing statistical test of age dates representing the main failure episode of the Holocene Storegga landslide complex.
Estimating the probability of rare events: addressing zero failure data.
Quigley, John; Revie, Matthew
2011-07-01
Traditional statistical procedures for estimating the probability of an event result in an estimate of zero when no events are realized. Alternative inferential procedures have been proposed for the situation where zero events have been realized but often these are ad hoc, relying on selecting methods dependent on the data that have been realized. Such data-dependent inference decisions violate fundamental statistical principles, resulting in estimation procedures whose benefits are difficult to assess. In this article, we propose estimating the probability of an event occurring through minimax inference on the probability that future samples of equal size realize no more events than that in the data on which the inference is based. Although motivated by inference on rare events, the method is not restricted to zero event data and closely approximates the maximum likelihood estimate (MLE) for nonzero data. The use of the minimax procedure provides a risk adverse inferential procedure where there are no events realized. A comparison is made with the MLE and regions of the underlying probability are identified where this approach is superior. Moreover, a comparison is made with three standard approaches to supporting inference where no event data are realized, which we argue are unduly pessimistic. We show that for situations of zero events the estimator can be simply approximated with 1/2.5n, where n is the number of trials. © 2011 Society for Risk Analysis.
Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid
2012-01-01
This paper discusses the estimation of the failure probability of wind turbines required by codes of practice for designing them. The Standard Monte Carlo (SMC) simulations may be used for this reason conceptually as an alternative to the popular Peaks-Over-Threshold (POT) method. However......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy...... is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated...
Recommendations for the tuning of rare event probability estimators
International Nuclear Information System (INIS)
Balesdent, Mathieu; Morio, Jérôme; Marzat, Julien
2015-01-01
Being able to accurately estimate rare event probabilities is a challenging issue in order to improve the reliability of complex systems. Several powerful methods such as importance sampling, importance splitting or extreme value theory have been proposed in order to reduce the computational cost and to improve the accuracy of extreme probability estimation. However, the performance of these methods is highly correlated with the choice of tuning parameters, which are very difficult to determine. In order to highlight recommended tunings for such methods, an empirical campaign of automatic tuning on a set of representative test cases is conducted for splitting methods. It allows to provide a reduced set of tuning parameters that may lead to the reliable estimation of rare event probability for various problems. The relevance of the obtained result is assessed on a series of real-world aerospace problems
Stochastic goal-oriented error estimation with memory
Ackmann, Jan; Marotzke, Jochem; Korn, Peter
2017-11-01
We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.
Internal Medicine residents use heuristics to estimate disease probability.
Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin
2015-01-01
Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. We randomized 55 Internal Medicine residents to different versions of four clinical vignettes and asked them to estimate probabilities of target conditions. We manipulated the clinical data for each vignette to be consistent with either 1) using a representative heuristic, by adding non-discriminating prototypical clinical features of the target condition, or 2) using anchoring with adjustment heuristic, by providing a high or low anchor for the target condition. When presented with additional non-discriminating data the odds of diagnosing the target condition were increased (odds ratio (OR) 2.83, 95% confidence interval [1.30, 6.15], p = 0.009). Similarly, the odds of diagnosing the target condition were increased when a high anchor preceded the vignette (OR 2.04, [1.09, 3.81], p = 0.025). Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.
Data error effects on net radiation and evapotranspiration estimation
International Nuclear Information System (INIS)
Llasat, M.C.; Snyder, R.L.
1998-01-01
The objective of this paper is to evaluate the potential error in estimating the net radiation and reference evapotranspiration resulting from errors in the measurement or estimation of weather parameters. A methodology for estimating the net radiation using hourly weather variables measured at a typical agrometeorological station (e.g., solar radiation, temperature and relative humidity) is presented. Then the error propagation analysis is made for net radiation and for reference evapotranspiration. Data from the Raimat weather station, which is located in the Catalonia region of Spain, are used to illustrate the error relationships. The results show that temperature, relative humidity and cloud cover errors have little effect on the net radiation or reference evapotranspiration. A 5°C error in estimating surface temperature leads to errors as big as 30 W m −2 at high temperature. A 4% solar radiation (R s ) error can cause a net radiation error as big as 26 W m −2 when R s ≈ 1000 W m −2 . However, the error is less when cloud cover is calculated as a function of the solar radiation. The absolute error in reference evapotranspiration (ET o ) equals the product of the net radiation error and the radiation term weighting factor [W = Δ(Δ1+γ)] in the ET o equation. Therefore, the ET o error varies between 65 and 85% of the R n error as air temperature increases from about 20° to 40°C. (author)
Allelic drop-out probabilities estimated by logistic regression
DEFF Research Database (Denmark)
Tvedebrink, Torben; Eriksen, Poul Svante; Asplund, Maria
2012-01-01
We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out...... is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions....
The calculation of average error probability in a digital fibre optical communication system
Rugemalira, R. A. M.
1980-03-01
This paper deals with the problem of determining the average error probability in a digital fibre optical communication system, in the presence of message dependent inhomogeneous non-stationary shot noise, additive Gaussian noise and intersymbol interference. A zero-forcing equalization receiver filter is considered. Three techniques for error rate evaluation are compared. The Chernoff bound and the Gram-Charlier series expansion methods are compared to the characteristic function technique. The latter predicts a higher receiver sensitivity
Error Estimation in Preconditioned Conjugate Gradients
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2005-01-01
Roč. 45, - (2005), s. 789-817 ISSN 0006-3835 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB1030306 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned conjugate gradient method * error bounds * stopping criteria * evaluation of convergence * numerical stability * finite precision arithmetic * rounding errors Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2005
On the average capacity and bit error probability of wireless communication systems
Yilmaz, Ferkan
2011-12-01
Analysis of the average binary error probabilities and average capacity of wireless communications systems over generalized fading channels have been considered separately in the past. This paper introduces a novel moment generating function-based unified expression for both average binary error probabilities and average capacity of single and multiple link communication with maximal ratio combining. It is a matter to note that the generic unified expression offered in this paper can be easily calculated and that is applicable to a wide variety of fading scenarios, and the mathematical formalism is illustrated with the generalized Gamma fading distribution in order to validate the correctness of our newly derived results. © 2011 IEEE.
Energy Technology Data Exchange (ETDEWEB)
Garza, J. [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States); Millwater, H., E-mail: harry.millwater@utsa.edu [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States)
2012-04-15
A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: Black-Right-Pointing-Pointer Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. Black-Right-Pointing-Pointer The sensitivities are computed with negligible cost using Monte Carlo sampling. Black-Right-Pointing-Pointer The change in the POF due to a change in the POD curve parameters can be easily estimated.
International Nuclear Information System (INIS)
Garza, J.; Millwater, H.
2012-01-01
A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: ► Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. ►The sensitivities are computed with negligible cost using Monte Carlo sampling. ► The change in the POF due to a change in the POD curve parameters can be easily estimated.
Estimation of failure probabilities of linear dynamic systems by ...
Indian Academy of Sciences (India)
An iterative method for estimating the failure probability for certain time-variant reliability problems has been developed. In the paper, the focus is on the displacement response of a linear oscillator driven by white noise. Failure is then assumed to occur when the displacement response exceeds a critical threshold.
Estimating the joint survival probabilities of married individuals
Sanders, Lisanne; Melenberg, Bertrand
We estimate the joint survival probability of spouses using a large random sample drawn from a Dutch census. As benchmarks we use two bivariate Weibull models. We consider more flexible models, using a semi-nonparametric approach, by extending the independent Weibull distribution using squared
Uncovering the Best Skill Multimap by Constraining the Error Probabilities of the Gain-Loss Model
Anselmi, Pasquale; Robusto, Egidio; Stefanutti, Luca
2012-01-01
The Gain-Loss model is a probabilistic skill multimap model for assessing learning processes. In practical applications, more than one skill multimap could be plausible, while none corresponds to the true one. The article investigates whether constraining the error probabilities is a way of uncovering the best skill assignment among a number of…
Modeling the probability distribution of positional errors incurred by residential address geocoding
Directory of Open Access Journals (Sweden)
Mazumdar Soumya
2007-01-01
Full Text Available Abstract Background The assignment of a point-level geocode to subjects' residences is an important data assimilation component of many geographic public health studies. Often, these assignments are made by a method known as automated geocoding, which attempts to match each subject's address to an address-ranged street segment georeferenced within a streetline database and then interpolate the position of the address along that segment. Unfortunately, this process results in positional errors. Our study sought to model the probability distribution of positional errors associated with automated geocoding and E911 geocoding. Results Positional errors were determined for 1423 rural addresses in Carroll County, Iowa as the vector difference between each 100%-matched automated geocode and its true location as determined by orthophoto and parcel information. Errors were also determined for 1449 60%-matched geocodes and 2354 E911 geocodes. Huge (> 15 km outliers occurred among the 60%-matched geocoding errors; outliers occurred for the other two types of geocoding errors also but were much smaller. E911 geocoding was more accurate (median error length = 44 m than 100%-matched automated geocoding (median error length = 168 m. The empirical distributions of positional errors associated with 100%-matched automated geocoding and E911 geocoding exhibited a distinctive Greek-cross shape and had many other interesting features that were not capable of being fitted adequately by a single bivariate normal or t distribution. However, mixtures of t distributions with two or three components fit the errors very well. Conclusion Mixtures of bivariate t distributions with few components appear to be flexible enough to fit many positional error datasets associated with geocoding, yet parsimonious enough to be feasible for nascent applications of measurement-error methodology to spatial epidemiology.
Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)
Adler, Robert; Gu, Guojun; Huffman, George
2012-01-01
different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.
Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory
Directory of Open Access Journals (Sweden)
Yafei Song
2015-01-01
Full Text Available Intuitionistic fuzzy (IF evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
COMPARATIVE ANALYSIS OF ESTIMATION METHODS OF PHARMACY ORGANIZATION BANKRUPTCY PROBABILITY
Directory of Open Access Journals (Sweden)
V. L. Adzhienko
2014-01-01
Full Text Available A purpose of this study was to determine the probability of bankruptcy by various methods in order to predict the financial crisis of pharmacy organization. Estimating the probability of pharmacy organization bankruptcy was conducted using W. Beaver’s method adopted in the Russian Federation, with integrated assessment of financial stability use on the basis of scoring analysis. The results obtained by different methods are comparable and show that the risk of bankruptcy of the pharmacy organization is small.
Failure probability estimate of type 304 stainless steel piping
International Nuclear Information System (INIS)
Daugherty, W.L.; Awadalla, N.G.; Sindelar, R.L.; Mehta, H.S.; Ranganath, S.
1989-01-01
The primary source of in-service degradation of the SRS production reactor process water piping is intergranular stress corrosion cracking (IGSCC). IGSCC has occurred in a limited number of weld heat affected zones, areas known to be susceptible to IGSCC. A model has been developed to combine crack growth rates, crack size distributions, in-service examination reliability estimates and other considerations to estimate the pipe large-break frequency. This frequency estimates the probability that an IGSCC crack will initiate, escape detection by ultrasonic (UT) examination, and grow to instability prior to extending through-wall and being detected by the sensitive leak detection system. These events are combined as the product of four factors: (1) the probability that a given weld heat affected zone contains IGSCC; (2) the conditional probability, given the presence of IGSCC, that the cracking will escape detection during UT examination; (3) the conditional probability, given a crack escapes detection by UT, that it will not grow through-wall and be detected by leakage; (4) the conditional probability, given a crack is not detected by leakage, that it grows to instability prior to the next UT exam. These four factors estimate the occurrence of several conditions that must coexist in order for a crack to lead to a large break of the process water piping. When evaluated for the SRS production reactors, they produce an extremely low break frequency. The objective of this paper is to present the assumptions, methodology, results and conclusions of a probabilistic evaluation for the direct failure of the primary coolant piping resulting from normal operation and seismic loads. This evaluation was performed to support the ongoing PRA effort and to complement deterministic analyses addressing the credibility of a double-ended guillotine break
Accuracy of crystal structure error estimates
International Nuclear Information System (INIS)
Taylor, R.; Kennard, O.
1986-01-01
A statistical analysis of 100 crystal structures retrieved from the Cambridge Structural Database is reported. Each structure has been determined independently by two different research groups. Comparison of the independent results leads to the following conclusions: (a) The e.s.d.'s of non-hydrogen-atom positional parameters are almost invariably too small. Typically, they are underestimated by a factor of 1.4-1.45. (b) The extent to which e.s.d.'s are underestimated varies significantly from structure to structure and from atom to atom within a structure. (c) Errors in the positional parameters of atoms belonging to the same chemical residue tend to be positively correlated. (d) The e.s.d.'s of heavy-atom positions are less reliable than those of light-atom positions. (e) Experimental errors in atomic positional parameters are normally, or approximately normally, distributed. (f) The e.s.d.'s of cell parameters are grossly underestimated, by an average factor of about 5 for cell lengths and 2.5 for cell angles. There is marginal evidence that the accuracy of atomic-coordinate e.s.d.'s also depends on diffractometer geometry, refinement procedure, whether or not the structure has a centre of symmetry, and the degree of precision attained in the structure determination. (orig.)
Collective animal behavior from Bayesian estimation and probability matching.
Directory of Open Access Journals (Sweden)
Alfonso Pérez-Escudero
2011-11-01
Full Text Available Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is mainly based on empirical fits to observations, with less emphasis in obtaining first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching. In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability equal to the Bayesian-estimated probability that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior.
Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains
Directory of Open Access Journals (Sweden)
Erik Van der Straeten
2009-11-01
Full Text Available In this paper, we develop a general theory for the estimation of the transition probabilities of reversible Markov chains using the maximum entropy principle. A broad range of physical models can be studied within this approach. We use one-dimensional classical spin systems to illustrate the theoretical ideas. The examples studied in this paper are: the Ising model, the Potts model and the Blume-Emery-Griffiths model.
Estimating probable flaw distributions in PWR steam generator tubes
International Nuclear Information System (INIS)
Gorman, J.A.; Turner, A.P.L.
1997-01-01
This paper describes methods for estimating the number and size distributions of flaws of various types in PWR steam generator tubes. These estimates are needed when calculating the probable primary to secondary leakage through steam generator tubes under postulated accidents such as severe core accidents and steam line breaks. The paper describes methods for two types of predictions: (1) the numbers of tubes with detectable flaws of various types as a function of time, and (2) the distributions in size of these flaws. Results are provided for hypothetical severely affected, moderately affected and lightly affected units. Discussion is provided regarding uncertainties and assumptions in the data and analyses
Estimating the exceedance probability of rain rate by logistic regression
Chiu, Long S.; Kedem, Benjamin
1990-01-01
Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.
Probability Density Estimation Using Neural Networks in Monte Carlo Calculations
International Nuclear Information System (INIS)
Shim, Hyung Jin; Cho, Jin Young; Song, Jae Seung; Kim, Chang Hyo
2008-01-01
The Monte Carlo neutronics analysis requires the capability for a tally distribution estimation like an axial power distribution or a flux gradient in a fuel rod, etc. This problem can be regarded as a probability density function estimation from an observation set. We apply the neural network based density estimation method to an observation and sampling weight set produced by the Monte Carlo calculations. The neural network method is compared with the histogram and the functional expansion tally method for estimating a non-smooth density, a fission source distribution, and an absorption rate's gradient in a burnable absorber rod. The application results shows that the neural network method can approximate a tally distribution quite well. (authors)
Arm locking with Doppler estimation errors
Energy Technology Data Exchange (ETDEWEB)
Yu Yinan; Wand, Vinzenz; Mitryk, Shawn; Mueller, Guido, E-mail: yinan@phys.ufl.ed [Department of Physics, University of Florida, Gainesville, FL 32611 (United States)
2010-05-01
At the University of Florida we developed the University of Florida LISA Interferometer Simulator (UFLIS) in order to study LISA interferometry with hardware in the loop at a system level. One of the proposed laser frequency stabilization techniques in LISA is arm locking. Arm locking uses an adequately filtered linear combination of the LISA arm signals as a frequency reference. We will report about experiments in which we demonstrated arm locking using UFLIS. During these experiments we also discovered a problem associated with the Doppler shift of the return beam. The initial arm locking publications assumed that this Doppler shift can perfectly be subtracted inside the phasemeter or adds an insignificant offset to the sensor signal. However, the remaining Doppler knowledge error will cause a constant change in the laser frequency if unaccounted for. Several ways to circumvent this problem have been identified. We performed detailed simulations and started preliminary experiments to verify the performance of the proposed new controller designs.
Error Estimation and Accuracy Improvements in Nodal Transport Methods
International Nuclear Information System (INIS)
Zamonsky, O.M.
2000-01-01
The accuracy of the solutions produced by the Discrete Ordinates neutron transport nodal methods is analyzed.The obtained new numerical methodologies increase the accuracy of the analyzed scheems and give a POSTERIORI error estimators. The accuracy improvement is obtained with new equations that make the numerical procedure free of truncation errors and proposing spatial reconstructions of the angular fluxes that are more accurate than those used until present. An a POSTERIORI error estimator is rigurously obtained for one dimensional systems that, in certain type of problems, allows to quantify the accuracy of the solutions. From comparisons with the one dimensional results, an a POSTERIORI error estimator is also obtained for multidimensional systems. LOCAL indicators, which quantify the spatial distribution of the errors, are obtained by the decomposition of the menctioned estimators. This makes the proposed methodology suitable to perform adaptive calculations. Some numerical examples are presented to validate the theoretical developements and to illustrate the ranges where the proposed approximations are valid
Approaches to relativistic positioning around Earth and error estimations
Puchades, Neus; Sáez, Diego
2016-01-01
In the context of relativistic positioning, the coordinates of a given user may be calculated by using suitable information broadcast by a 4-tuple of satellites. Our 4-tuples belong to the Galileo constellation. Recently, we estimated the positioning errors due to uncertainties in the satellite world lines (U-errors). A distribution of U-errors was obtained, at various times, in a set of points covering a large region surrounding Earth. Here, the positioning errors associated to the simplifying assumption that photons move in Minkowski space-time (S-errors) are estimated and compared with the U-errors. Both errors have been calculated for the same points and times to make comparisons possible. For a certain realistic modeling of the world line uncertainties, the estimated S-errors have proved to be smaller than the U-errors, which shows that the approach based on the assumption that the Earth's gravitational field produces negligible effects on photons may be used in a large region surrounding Earth. The applicability of this approach - which simplifies numerical calculations - to positioning problems, and the usefulness of our S-error maps, are pointed out. A better approach, based on the assumption that photons move in the Schwarzschild space-time governed by an idealized Earth, is also analyzed. More accurate descriptions of photon propagation involving non symmetric space-time structures are not necessary for ordinary positioning and spacecraft navigation around Earth.
Estimation of the measurement error of eccentrically installed orifice plates
Energy Technology Data Exchange (ETDEWEB)
Barton, Neil; Hodgkinson, Edwin; Reader-Harris, Michael
2005-07-01
The presentation discusses methods for simulation and estimation of flow measurement errors. The main conclusions are: Computational Fluid Dynamics (CFD) simulation methods and published test measurements have been used to estimate the error of a metering system over a period when its orifice plates were eccentric and when leaking O-rings allowed some gas to bypass the meter. It was found that plate eccentricity effects would result in errors of between -2% and -3% for individual meters. Validation against test data suggests that these estimates of error should be within 1% of the actual error, but it is unclear whether the simulations over-estimate or under-estimate the error. Simulations were also run to assess how leakage at the periphery affects the metering error. Various alternative leakage scenarios were modelled and it was found that the leakage rate has an effect on the error, but that the leakage distribution does not. Correction factors, based on the CFD results, were then used to predict the system's mis-measurement over a three-year period (tk)
Fast Outage Probability Simulation for FSO Links with a Generalized Pointing Error Model
Ben Issaid, Chaouki
2017-02-07
Over the past few years, free-space optical (FSO) communication has gained significant attention. In fact, FSO can provide cost-effective and unlicensed links, with high-bandwidth capacity and low error rate, making it an exciting alternative to traditional wireless radio-frequency communication systems. However, the system performance is affected not only by the presence of atmospheric turbulences, which occur due to random fluctuations in the air refractive index but also by the existence of pointing errors. Metrics, such as the outage probability which quantifies the probability that the instantaneous signal-to-noise ratio is smaller than a given threshold, can be used to analyze the performance of this system. In this work, we consider weak and strong turbulence regimes, and we study the outage probability of an FSO communication system under a generalized pointing error model with both a nonzero boresight component and different horizontal and vertical jitter effects. More specifically, we use an importance sampling approach which is based on the exponential twisting technique to offer fast and accurate results.
On the dipole approximation with error estimates
Boßmann, Lea; Grummt, Robert; Kolb, Martin
2018-01-01
The dipole approximation is employed to describe interactions between atoms and radiation. It essentially consists of neglecting the spatial variation of the external field over the atom. Heuristically, this is justified by arguing that the wavelength is considerably larger than the atomic length scale, which holds under usual experimental conditions. We prove the dipole approximation in the limit of infinite wavelengths compared to the atomic length scale and estimate the rate of convergence. Our results include N-body Coulomb potentials and experimentally relevant electromagnetic fields such as plane waves and laser pulses.
Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods
Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.
2014-12-01
Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.
Estimation of Total Error in DWPF Reported Radionuclide Inventories
International Nuclear Information System (INIS)
Edwards, T.B.
1995-01-01
This report investigates the impact of random errors due to measurement and sampling on the reported concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch. The objective of this investigation is to estimate the variance of the total error in reporting these radionuclide concentrations
Error Estimation for Indoor 802.11 Location Fingerprinting
DEFF Research Database (Denmark)
Lemelson, Hendrik; Kjærgaard, Mikkel Baun; Hansen, Rene
2009-01-01
providers could adapt their delivered services based on the estimated position error to achieve a higher service quality. Finally, system operators could use the information to inspect whether a location system provides satisfactory positioning accuracy throughout the covered area. For position error...
NDE errors and their propagation in sizing and growth estimates
International Nuclear Information System (INIS)
Horn, D.; Obrutsky, L.; Lakhan, R.
2009-01-01
The accuracy attributed to eddy current flaw sizing determines the amount of conservativism required in setting tube-plugging limits. Several sources of error contribute to the uncertainty of the measurements, and the way in which these errors propagate and interact affects the overall accuracy of the flaw size and flaw growth estimates. An example of this calculation is the determination of an upper limit on flaw growth over one operating period, based on the difference between two measurements. Signal-to-signal comparison involves a variety of human, instrumental, and environmental error sources; of these, some propagate additively and some multiplicatively. In a difference calculation, specific errors in the first measurement may be correlated with the corresponding errors in the second; others may be independent. Each of the error sources needs to be identified and quantified individually, as does its distribution in the field data. A mathematical framework for the propagation of the errors can then be used to assess the sensitivity of the overall uncertainty to each individual error component. This paper quantifies error sources affecting eddy current sizing estimates and presents analytical expressions developed for their effect on depth estimates. A simple case study is used to model the analysis process. For each error source, the distribution of the field data was assessed and propagated through the analytical expressions. While the sizing error obtained was consistent with earlier estimates and with deviations from ultrasonic depth measurements, the error on growth was calculated as significantly smaller than that obtained assuming uncorrelated errors. An interesting result of the sensitivity analysis in the present case study is the quantification of the error reduction available from post-measurement compensation of magnetite effects. With the absolute and difference error equations, variance-covariance matrices, and partial derivatives developed in
Estimation of error fields from ferromagnetic parts in ITER
Energy Technology Data Exchange (ETDEWEB)
Oliva, A. Bonito [Fusion for Energy (Spain); Chiariello, A.G.; Formisano, A.; Martone, R. [Ass. EURATOM/ENEA/CREATE, Dip. di Ing. Industriale e dell’Informazione, Seconda Università di Napoli, Via Roma 29, I-81031 Napoli (Italy); Portone, A., E-mail: alfredo.portone@f4e.europa.eu [Fusion for Energy (Spain); Testoni, P. [Fusion for Energy (Spain)
2013-10-15
Highlights: ► The paper deals with error fields generated in ITER by magnetic masses. ► Magnetization state is computed from simplified FEM models. ► Closed form expressions adopted for the flux density of magnetized parts are given. ► Such expressions allow to simplify the estimation of the effect of iron pieces (or lack of) on error field. -- Abstract: Error fields in tokamaks are small departures from the exact axisymmetry of the ideal magnetic field configuration. Their reduction below a threshold value by the error field correction coils is essential since sufficiently large static error fields lead to discharge disruption. The error fields are originated not only by magnets fabrication and installation tolerances, by the joints and by the busbars, but also by the presence of ferromagnetic elements. It was shown that superconducting joints, feeders and busbars play a secondary effect; however in order to estimate of the importance of each possible error field source, rough evaluations can be very useful because it can provide an order of magnitude of the correspondent effect and, therefore, a ranking in the request for in depth analysis. The paper proposes a two steps procedure. The first step aims to get the approximate magnetization state of ferromagnetic parts; the second aims to estimate the full 3D error field over the whole volume using equivalent sources for magnetic masses and taking advantage from well assessed approximate closed form expressions, well suited for the far distance effects.
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Knock probability estimation through an in-cylinder temperature model with exogenous noise
Bares, P.; Selmanaj, D.; Guardiola, C.; Onder, C.
2018-01-01
This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in-cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1 % were found.
A Balanced Approach to Adaptive Probability Density Estimation
Directory of Open Access Journals (Sweden)
Julio A. Kovacs
2017-04-01
Full Text Available Our development of a Fast (Mutual Information Matching (FIM of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a random variable, especially in cases of very uneven samples. Here, we propose a novel Balanced Adaptive Density Estimation (BADE method that effectively optimizes the amount of smoothing at each point. To do this, BADE relies on an efficient nearest-neighbor search which results in good scaling for large data sizes. Our tests on simulated data show that BADE exhibits equal or better accuracy than existing methods, and visual tests on univariate and bivariate experimental data show that the results are also aesthetically pleasing. This is due in part to the use of a visual criterion for setting the smoothing level of the density estimate. Our results suggest that BADE offers an attractive new take on the fundamental density estimation problem in statistics. We have applied it on molecular dynamics simulations of membrane pore formation. We also expect BADE to be generally useful for low-dimensional applications in other statistical application domains such as bioinformatics, signal processing and econometrics.
Verification of “Channel-Probability Model” of Grain Yield Estimation
Directory of Open Access Journals (Sweden)
ZHENG Hong-yan
2016-07-01
Full Text Available The "channel-probability model" of grain yield estimation was verified and discussed systematically by using the grain production data from 1949 to 2014 in 16 typical counties, and 6 typical districts, and 31 provinces of China. The results showed as follows:(1Due to the geographical spatial scale was large enough, different climate zones and different meteorological conditions could compensated, and grain yield estimation error was small in the scale of nation. Therefore, it was not necessary to modify the grain yield estimation error by mirco-trend and the climate year types in the scale of nation. However, the grain yield estimation in the scale of province was located at the same of a climate zone,the scale was small, so the impact of the meteorological conditions on grain yield was less complementary than the scale of nation. While the spatial scale of districts and counties was smaller, accordingly the compensation of the impact of the meteorological conditions on grain yield was least. Therefore, it was necessary to use mrico-trend amendment and the climate year types amendment to modify the grain yield estimation in districts and counties.(2Mirco-trend modification had two formulas, generally, when the error of grain yield estimation was less than 10%, it could be modified by Y×(1-K; while the error of grain yield estimation was more than 10%, it could be modified by Y/(1+K.(3Generally, the grain estimation had 5 grades, and some had 7 grades because of large error fluctuation. The parameters modified of super-high yield year and super-low yield year must be depended on the real-time crop growth and the meteorological condition. (4By plenty of demonstration analysis, it was proved that the theory and method of "channel-probability model" was scientific and practical. In order to improve the accuracy of grain yield estimation, the parameters could be modified with micro-trend amendment and the climate year types amendment. If the
Time of Arrival Estimation in Probability-Controlled Generalized CDMA Systems
Directory of Open Access Journals (Sweden)
Hagit Messer
2007-11-01
Full Text Available In recent years, more and more wireless communications systems are required to provide also a positioning measurement. In code division multiple access (CDMA communication systems, the positioning accuracy is significantly degraded by the multiple access interference (MAI caused by other users in the system. This MAI is commonly managed by a power control mechanism, and yet, MAI has a major effect on positioning accuracy. Probability control is a recently introduced interference management mechanism. In this mechanism, a user with excess power chooses not to transmit some of its symbols. The information in the nontransmitted symbols is recovered by an error-correcting code (ECC, while all other users receive a more reliable data during these quiet periods. Previous research had shown that the implementation of a probability control mechanism can significantly reduce the MAI. In this paper, we show that probability control also improves the positioning accuracy. We focus on time-of-arrival (TOA based positioning systems. We analyze the TOA estimation performance in a generalized CDMA system, in which the probability control mechanism is employed, where the transmitted signal is noncontinuous with a symbol transmission probability smaller than 1. The accuracy of the TOA estimation is determined using appropriate modifications of the Cramer-Rao bound on the delay estimation. Keeping the average transmission power constant, we show that the TOA accuracy of each user does not depend on its transmission probability, while being a nondecreasing function of the transmission probability of any other user. Therefore, a generalized, noncontinuous CDMA system with a probability control mechanism can always achieve better positioning performance, for all users in the network, than a conventional, continuous, CDMA system.
The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence
Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo
2018-05-01
The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.
Minimum Probability of Error-Based Equalization Algorithms for Fading Channels
Directory of Open Access Journals (Sweden)
Janos Levendovszky
2007-06-01
Full Text Available Novel channel equalizer algorithms are introduced for wireless communication systems to combat channel distortions resulting from multipath propagation. The novel algorithms are based on newly derived bounds on the probability of error (PE and guarantee better performance than the traditional zero forcing (ZF or minimum mean square error (MMSE algorithms. The new equalization methods require channel state information which is obtained by a fast adaptive channel identification algorithm. As a result, the combined convergence time needed for channel identification and PE minimization still remains smaller than the convergence time of traditional adaptive algorithms, yielding real-time equalization. The performance of the new algorithms is tested by extensive simulations on standard mobile channels.
Directory of Open Access Journals (Sweden)
Juan Mario Torres Nova
2008-09-01
Full Text Available Gaussian minimum shift keying (GMSK and differential binary phase shift keying (DBPSK are two digital modulation schemes which are -frequently used in radio communication systems; however, there is interdependence in the use of its benefits (spectral efficiency, low bit error rate, low inter symbol interference, etc. Optimising one parameter creates problems for another; for example, the GMSK scheme succeeds in reducing bandwidth when introducing a Gaussian filter into an MSK (minimum shift ke-ying modulator in exchange for increasing inter-symbol interference in the system. The DBPSK scheme leads to lower error pro-bability, occupying more bandwidth; it likewise facilitates synchronous data transmission due to the receiver’s bit delay when re-covering a signal.
Site Specific Probable Maximum Precipitation Estimates and Professional Judgement
Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.
2015-12-01
State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially
Directory of Open Access Journals (Sweden)
Duong Trung Q
2007-01-01
Full Text Available We analyze the exact average symbol error probability (SEP of binary and -ary signals with spatial diversity in Nakagami- (Hoyt fading channels. The maximal-ratio combining and orthogonal space-time block coding are considered as diversity techniques for single-input multiple-output and multiple-input multiple-output systems, respectively. We obtain the average SEP in terms of the Lauricella multivariate hypergeometric function . The analysis is verified by comparing with Monte Carlo simulations and we further show that our general SEP expressions particularize to the previously known results for Rayleigh ( = 1 and single-input single-output (SISO Nakagami- cases.
Brus, D.J.; Gruijter, de J.J.
2003-01-01
In estimating spatial means of environmental variables of a region from data collected by convenience or purposive sampling, validity of the results can be ensured by collecting additional data through probability sampling. The precision of the pi estimator that uses the probability sample can be
Estimating the Autocorrelated Error Model with Trended Data: Further Results,
1979-11-01
Perhaps the most serious deficiency of OLS in the presence of autocorrelation is not inefficiency but bias in its estimated standard errors--a bias...k for all t has variance var(b) = o2/ Tk2 2This refutes Maeshiro’s (1976) conjecture that "an estimator utilizing relevant extraneous information
NESTEM-QRAS: A Tool for Estimating Probability of Failure
Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.
2002-10-01
An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.
NESTEM-QRAS: A Tool for Estimating Probability of Failure
Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.
2002-01-01
An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.
On the prior probabilities for two-stage Bayesian estimates
International Nuclear Information System (INIS)
Kohut, P.
1992-01-01
The method of Bayesian inference is reexamined for its applicability and for the required underlying assumptions in obtaining and using prior probability estimates. Two different approaches are suggested to determine the first-stage priors in the two-stage Bayesian analysis which avoid certain assumptions required for other techniques. In the first scheme, the prior is obtained through a true frequency based distribution generated at selected intervals utilizing actual sampling of the failure rate distributions. The population variability distribution is generated as the weighed average of the frequency distributions. The second method is based on a non-parametric Bayesian approach using the Maximum Entropy Principle. Specific features such as integral properties or selected parameters of prior distributions may be obtained with minimal assumptions. It is indicated how various quantiles may also be generated with a least square technique
[Survival analysis with competing risks: estimating failure probability].
Llorca, Javier; Delgado-Rodríguez, Miguel
2004-01-01
To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.
Directory of Open Access Journals (Sweden)
Hina Nasir
2016-07-01
Full Text Available This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs; performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE efficient depth based routing and Enhanced-ACE (E-ACE are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ. E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment.
Mean value estimates of the error terms of Lehmer problem
Indian Academy of Sciences (India)
Mean value estimates of the error terms of Lehmer problem. DONGMEI REN1 and YAMING ... For further properties of N(a,p) in [6], he studied the mean square value of the error term. E(a, p) = N(a,p) − 1. 2 (p − 1) ..... [1] Apostol Tom M, Introduction to Analytic Number Theory (New York: Springer-Verlag). (1976). [2] Guy R K ...
Complementarity based a posteriori error estimates and their properties
Czech Academy of Sciences Publication Activity Database
Vejchodský, Tomáš
2012-01-01
Roč. 82, č. 10 (2012), s. 2033-2046 ISSN 0378-4754 R&D Projects: GA ČR(CZ) GA102/07/0496; GA AV ČR IAA100760702 Institutional research plan: CEZ:AV0Z10190503 Keywords : error majorant * a posteriori error estimates * method of hypercircle Subject RIV: BA - General Mathematics Impact factor: 0.836, year: 2012 http://www.sciencedirect.com/science/article/pii/S0378475411001509
Estimation of subcriticality of TCA using 'indirect estimation method for calculation error'
International Nuclear Information System (INIS)
Naito, Yoshitaka; Yamamoto, Toshihiro; Arakawa, Takuya; Sakurai, Kiyoshi
1996-01-01
To estimate the subcriticality of neutron multiplication factor in a fissile system, 'Indirect Estimation Method for Calculation Error' is proposed. This method obtains the calculational error of neutron multiplication factor by correlating measured values with the corresponding calculated ones. This method was applied to the source multiplication and to the pulse neutron experiments conducted at TCA, and the calculation error of MCNP 4A was estimated. In the source multiplication method, the deviation of measured neutron count rate distributions from the calculated ones estimates the accuracy of calculated k eff . In the pulse neutron method, the calculation errors of prompt neutron decay constants give the accuracy of the calculated k eff . (author)
The estimation of probable maximum precipitation: the case of Catalonia.
Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel
2008-12-01
A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.
Shiryaev, A N
1996-01-01
This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables
Verification of unfold error estimates in the unfold operator code
International Nuclear Information System (INIS)
Fehl, D.L.; Biggs, F.
1997-01-01
Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5% (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. copyright 1997 American Institute of Physics
An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.
Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan
2017-11-18
Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio
Aniseikonia quantification: error rate of rule of thumb estimation.
Lubkin, V; Shippman, S; Bennett, G; Meininger, D; Kramer, P; Poppinga, P
1999-01-01
To find the error rate in quantifying aniseikonia by using "Rule of Thumb" estimation in comparison with proven space eikonometry. Study 1: 24 adult pseudophakic individuals were measured for anisometropia, and astigmatic interocular difference. Rule of Thumb quantification for prescription was calculated and compared with aniseikonia measurement by the classical Essilor Projection Space Eikonometer. Study 2: parallel analysis was performed on 62 consecutive phakic patients from our strabismus clinic group. Frequency of error: For Group 1 (24 cases): 5 ( or 21 %) were equal (i.e., 1% or less difference); 16 (or 67% ) were greater (more than 1% different); and 3 (13%) were less by Rule of Thumb calculation in comparison to aniseikonia determined on the Essilor eikonometer. For Group 2 (62 cases): 45 (or 73%) were equal (1% or less); 10 (or 16%) were greater; and 7 (or 11%) were lower in the Rule of Thumb calculations in comparison to Essilor eikonometry. Magnitude of error: In Group 1, in 10/24 (29%) aniseikonia by Rule of Thumb estimation was 100% or more greater than by space eikonometry, and in 6 of those ten by 200% or more. In Group 2, in 4/62 (6%) aniseikonia by Rule of Thumb estimation was 200% or more greater than by space eikonometry. The frequency and magnitude of apparent clinical errors of Rule of Thumb estimation is disturbingly large. This problem is greatly magnified by the time and effort and cost of prescribing and executing an aniseikonic correction for a patient. The higher the refractive error, the greater the anisometropia, and the worse the errors in Rule of Thumb estimation of aniseikonia. Accurate eikonometric methods and devices should be employed in all cases where such measurements can be made. Rule of thumb estimations should be limited to cases where such subjective testing and measurement cannot be performed, as in infants after unilateral cataract surgery.
Joseph, Maria L; Carriquiry, Alicia
2010-11-01
Collection of dietary intake information requires time-consuming and expensive methods, making it inaccessible to many resource-poor countries. Quantifying the association between simple measures of usual dietary diversity and usual nutrient intake/adequacy would allow inferences to be made about the adequacy of micronutrient intake at the population level for a fraction of the cost. In this study, we used secondary data from a dietary intake study carried out in Bangladesh to assess the association between 3 food group diversity indicators (FGI) and calcium intake; and the association between these same 3 FGI and a composite measure of nutrient adequacy, mean probability of adequacy (MPA). By implementing Fuller's error-in-the-equation measurement error model (EEM) and simple linear regression (SLR) models, we assessed these associations while accounting for the error in the observed quantities. Significant associations were detected between usual FGI and usual calcium intakes, when the more complex EEM was used. The SLR model detected significant associations between FGI and MPA as well as for variations of these measures, including the best linear unbiased predictor. Through simulation, we support the use of the EEM. In contrast to the EEM, the SLR model does not account for the possible correlation between the measurement errors in the response and predictor. The EEM performs best when the model variables are not complex functions of other variables observed with error (e.g. MPA). When observation days are limited and poor estimates of the within-person variances are obtained, the SLR model tends to be more appropriate.
Influence of measurement errors and estimated parameters on combustion diagnosis
International Nuclear Information System (INIS)
Payri, F.; Molina, S.; Martin, J.; Armas, O.
2006-01-01
Thermodynamic diagnosis models are valuable tools for the study of Diesel combustion. Inputs required by such models comprise measured mean and instantaneous variables, together with suitable values for adjustable parameters used in different submodels. In the case of measured variables, one may estimate the uncertainty associated with measurement errors; however, the influence of errors in model parameter estimation may not be so easily established on an experimental basis. In this paper, a simulated pressure cycle has been used along with known input parameters, so that any uncertainty in the inputs is avoided. Then, the influence of errors in measured variables and geometric and heat transmission parameters on the results of a diagnosis combustion model for direct injection diesel engines have been studied. This procedure allowed to establish the relative importance of these parameters and to set limits to the maximal errors of the model, accounting for both the maximal expected errors in the input parameters and the sensitivity of the model to those errors
Error Estimation for the Linearized Auto-Localization Algorithm
Directory of Open Access Journals (Sweden)
Fernando Seco
2012-02-01
Full Text Available The Linearized Auto-Localization (LAL algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs, using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL, the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.
Directory of Open Access Journals (Sweden)
Madeiro Francisco
2010-01-01
Full Text Available Abstract This paper presents an alternative method for determining exact expressions for the bit error probability (BEP of modulation schemes subject to Nakagami- fading. In this method, the Nakagami- fading channel is seen as an additive noise channel whose noise is modeled as the ratio between Gaussian and Nakagami- random variables. The method consists of using the cumulative density function of the resulting noise to obtain closed-form expressions for the BEP of modulation schemes subject to Nakagami- fading. In particular, the proposed method is used to obtain closed-form expressions for the BEP of -ary quadrature amplitude modulation ( -QAM, -ary pulse amplitude modulation ( -PAM, and rectangular quadrature amplitude modulation ( -QAM under Nakagami- fading. The main contribution of this paper is to show that this alternative method can be used to reduce the computational complexity for detecting signals in the presence of fading.
Symbol Error Probability of DF Relay Selection over Arbitrary Nakagami-m Fading Channels
Directory of Open Access Journals (Sweden)
George C. Alexandropoulos
2013-01-01
Full Text Available We present a new analytical expression for the moment generating function (MGF of the end-to-end signal-to-noise ratio of dual-hop decode-and-forward (DF relaying systems with relay selection when operating over Nakagami-m fading channels. The derived MGF expression, which is valid for arbitrary values of the fading parameters of both hops, is subsequently utilized to evaluate the average symbol error probability (ASEP of M-ary phase shift keying modulation for the considered DF relaying scheme under various asymmetric fading conditions. It is shown that the MGF-based ASEP performance evaluation results are in excellent agreement with equivalent ones obtained by means of computer simulations, thus validating the correctness of the presented MGF expression.
Structural health monitoring and probability of detection estimation
Forsyth, David S.
2016-02-01
Structural health monitoring (SHM) methods are often based on nondestructive testing (NDT) sensors and are often proposed as replacements for NDT to lower cost and/or improve reliability. In order to take advantage of SHM for life cycle management, it is necessary to determine the Probability of Detection (POD) of the SHM system just as for traditional NDT to ensure that the required level of safety is maintained. Many different possibilities exist for SHM systems, but one of the attractive features of SHM versus NDT is the ability to take measurements very simply after the SHM system is installed. Using a simple statistical model of POD, some authors have proposed that very high rates of SHM system data sampling can result in high effective POD even in situations where an individual test has low POD. In this paper, we discuss the theoretical basis for determining the effect of repeated inspections, and examine data from SHM experiments against this framework to show how the effective POD from multiple tests can be estimated.
On global error estimation and control for initial value problems
J. Lang (Jens); J.G. Verwer (Jan)
2007-01-01
textabstractThis paper addresses global error estimation and control for initial value problems for ordinary differential equations. The focus lies on a comparison between a novel approach based onthe adjoint method combined with a small sample statistical initialization and the classical approach
On global error estimation and control for initial value problems
Lang, J.; Verwer, J.G.
2007-01-01
Abstract. This paper addresses global error estimation and control for initial value problems for ordinary differential equations. The focus lies on a comparison between a novel approach based on the adjoint method combined with a small sample statistical initialization and the classical approach
Bayesian error estimation in density-functional theory
DEFF Research Database (Denmark)
Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund
2005-01-01
We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...
A posteriori error estimates for axisymmetric and nonlinear problems
Czech Academy of Sciences Publication Activity Database
Křížek, Michal; Němec, J.; Vejchodský, Tomáš
2001-01-01
Roč. 15, - (2001), s. 219-236 ISSN 1019-7168 R&D Projects: GA ČR GA201/01/1200; GA MŠk ME 148 Keywords : weigted Sobolev spaces%a posteriori error estimates%finite elements Subject RIV: BA - General Mathematics Impact factor: 0.886, year: 2001
Error estimates in horocycle averages asymptotics: challenges from string theory
Cardella, M.A.
2010-01-01
For modular functions of rapid decay, a classical result connects the error estimate in their long horocycle average asymptotic to the Riemann hypothesis. We study similar asymptotics, for modular functions with not that mild growing conditions, such as of polynomial growth and of exponential growth
Computational Error Estimate for the Power Series Solution of Odes ...
African Journals Online (AJOL)
This paper compares the error estimation of power series solution with recursive Tau method for solving ordinary differential equations. From the computational viewpoint, the power series using zeros of Chebyshevpolunomial is effective, accurate and easy to use. Keywords: Lanczos Tau method, Chebyshev polynomial, ...
Error Estimates for the Approximation of the Effective Hamiltonian
International Nuclear Information System (INIS)
Camilli, Fabio; Capuzzo Dolcetta, Italo; Gomes, Diogo A.
2008-01-01
We study approximation schemes for the cell problem arising in homogenization of Hamilton-Jacobi equations. We prove several error estimates concerning the rate of convergence of the approximation scheme to the effective Hamiltonian, both in the optimal control setting and as well as in the calculus of variations setting
SIMULATED HUMAN ERROR PROBABILITY AND ITS APPLICATION TO DYNAMIC HUMAN FAILURE EVENTS
Energy Technology Data Exchange (ETDEWEB)
Herberger, Sarah M.; Boring, Ronald L.
2016-10-01
Abstract Objectives: Human reliability analysis (HRA) methods typically analyze human failure events (HFEs) at the overall task level. For dynamic HRA, it is important to model human activities at the subtask level. There exists a disconnect between dynamic subtask level and static task level that presents issues when modeling dynamic scenarios. For example, the SPAR-H method is typically used to calculate the human error probability (HEP) at the task level. As demonstrated in this paper, quantification in SPAR-H does not translate to the subtask level. Methods: Two different discrete distributions were generated for each SPAR-H Performance Shaping Factor (PSF) to define the frequency of PSF levels. The first distribution was a uniform, or uninformed distribution that assumed the frequency of each PSF level was equally likely. The second non-continuous distribution took the frequency of PSF level as identified from an assessment of the HERA database. These two different approaches were created to identify the resulting distribution of the HEP. The resulting HEP that appears closer to the known distribution, a log-normal centered on 1E-3, is the more desirable. Each approach then has median, average and maximum HFE calculations applied. To calculate these three values, three events, A, B and C are generated from the PSF level frequencies comprised of subtasks. The median HFE selects the median PSF level from each PSF and calculates HEP. The average HFE takes the mean PSF level, and the maximum takes the maximum PSF level. The same data set of subtask HEPs yields starkly different HEPs when aggregated to the HFE level in SPAR-H. Results: Assuming that each PSF level in each HFE is equally likely creates an unrealistic distribution of the HEP that is centered at 1. Next the observed frequency of PSF levels was applied with the resulting HEP behaving log-normally with a majority of the values under 2.5% HEP. The median, average and maximum HFE calculations did yield
A Comparison of Error Bounds for a Nonlinear Tracking System with Detection Probability Pd < 1
Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin
2012-01-01
Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds. PMID:23242274
International Nuclear Information System (INIS)
Jang, Inseok; Kim, Ar Ryum; Jung, Wondea; Seong, Poong Hyun
2014-01-01
Highlights: • Many researchers have tried to understand human recovery process or step. • Modeling human recovery process is not sufficient to be applied to HRA. • The operation environment of MCRs in NPPs has changed by adopting new HSIs. • Recovery failure probability in a soft control operation environment is investigated. • Recovery failure probability here would be important evidence for expert judgment. - Abstract: It is well known that probabilistic safety assessments (PSAs) today consider not just hardware failures and environmental events that can impact upon risk, but also human error contributions. Consequently, the focus on reliability and performance management has been on the prevention of human errors and failures rather than the recovery of human errors. However, the recovery of human errors is as important as the prevention of human errors and failures for the safe operation of nuclear power plants (NPPs). For this reason, many researchers have tried to find a human recovery process or step. However, modeling the human recovery process is not sufficient enough to be applied to human reliability analysis (HRA), which requires human error and recovery probabilities. In this study, therefore, human error recovery failure probabilities based on predefined human error modes were investigated by conducting experiments in the operation mockup of advanced/digital main control rooms (MCRs) in NPPs. To this end, 48 subjects majoring in nuclear engineering participated in the experiments. In the experiments, using the developed accident scenario based on tasks from the standard post trip action (SPTA), the steam generator tube rupture (SGTR), and predominant soft control tasks, which are derived from the loss of coolant accident (LOCA) and the excess steam demand event (ESDE), all error detection and recovery data based on human error modes were checked with the performance sheet and the statistical analysis of error recovery/detection was then
Dental age estimation: the role of probability estimates at the 10 year threshold.
Lucas, Victoria S; McDonald, Fraser; Neil, Monica; Roberts, Graham
2014-08-01
The use of probability at the 18 year threshold has simplified the reporting of dental age estimates for emerging adults. The availability of simple to use widely available software has enabled the development of the probability threshold for individual teeth in growing children. Tooth development stage data from a previous study at the 10 year threshold were reused to estimate the probability of developing teeth being above or below the 10 year thresh-hold using the NORMDIST Function in Microsoft Excel. The probabilities within an individual subject are averaged to give a single probability that a subject is above or below 10 years old. To test the validity of this approach dental panoramic radiographs of 50 female and 50 male children within 2 years of the chronological age were assessed with the chronological age masked. Once the whole validation set of 100 radiographs had been assessed the masking was removed and the chronological age and dental age compared. The dental age was compared with chronological age to determine whether the dental age correctly or incorrectly identified a validation subject as above or below the 10 year threshold. The probability estimates correctly identified children as above or below on 94% of occasions. Only 2% of the validation group with a chronological age of less than 10 years were assigned to the over 10 year group. This study indicates the very high accuracy of assignment at the 10 year threshold. Further work at other legally important age thresholds is needed to explore the value of this approach to the technique of age estimation. Copyright © 2014. Published by Elsevier Ltd.
Evaluation of human error estimation for nuclear power plants
International Nuclear Information System (INIS)
Haney, L.N.; Blackman, H.S.
1987-01-01
The dominant risk for severe accident occurrence in nuclear power plants (NPPs) is human error. The US Nuclear Regulatory Commission (NRC) sponsored an evaluation of Human Reliability Analysis (HRA) techniques for estimation of human error in NPPs. Twenty HRA techniques identified by a literature search were evaluated with criteria sets designed for that purpose and categorized. Data were collected at a commercial NPP with operators responding in walkthroughs of four severe accident scenarios and full scope simulator runs. Results suggest a need for refinement and validation of the techniques. 19 refs
First hitting probabilities for semi markov chains and estimation
DEFF Research Database (Denmark)
Georgiadis, Stylianos
2017-01-01
We first consider a stochastic system described by an absorbing semi-Markov chain with finite state space and we introduce the absorption probability to a class of recurrent states. Afterwards, we study the first hitting probability to a subset of states for an irreducible semi-Markov chain...
International Nuclear Information System (INIS)
Vincent, C.H.
1982-01-01
Bayes' principle is applied to the differential counting measurement of a positive quantity in which the statistical errors are not necessarily small in relation to the true value of the quantity. The methods of estimation derived are found to give consistent results and to avoid the anomalous negative estimates sometimes obtained by conventional methods. One of the methods given provides a simple means of deriving the required estimates from conventionally presented results and appears to have wide potential applications. Both methods provide the actual posterior probability distribution of the quantity to be measured. A particularly important potential application is the correction of counts on low radioacitvity samples for background. (orig.)
An estimate and evaluation of design error effects on nuclear power plant design adequacy
International Nuclear Information System (INIS)
Stevenson, J.D.
1984-01-01
An area of considerable concern in evaluating Design Control Quality Assurance procedures applied to design and analysis of nuclear power plant is the level of design error expected or encountered. There is very little published data 1 on the level of error typically found in nuclear power plant design calculations and even less on the impact such errors would be expected to have on overall design adequacy of the plant. This paper is concerned with design error associated with civil and mechanical structural design and analysis found in calculations which form part of the Design or Stress reports. These reports are meant to document the design basis and adequacy of the plant. The estimates contained in this paper are based on the personal experiences of the author. In Table 1 is a partial listing of the design docummentation review performed by the author on which the observations contained in this paper are based. In the preparation of any design calculations, it is a utopian dream to presume such calculations can be made error free. The intent of this paper is to define error levels which might be expected in a competent engineering organizations employing currently technically qualified engineers and accepted methods of Design Control. In addition, the effects of these errors on the probability of failure to meet applicable design code requirements also are estimated
Directory of Open Access Journals (Sweden)
2012-12-01
Full Text Available Introduction: Emergency situation is one of the influencing factors on human error. The aim of this research was purpose to evaluate human error in emergency situation of fire and explosion at the oil company warehouse in Hamadan city applying human error probability index (HEPI. . Material and Method: First, the scenario of emergency situation of those situation of fire and explosion at the oil company warehouse was designed and then maneuver against, was performed. The scaled questionnaire of muster for the maneuver was completed in the next stage. Collected data were analyzed to calculate the probability success for the 18 actions required in an emergency situation from starting point of the muster until the latest action to temporary sheltersafe. .Result: The result showed that the highest probability of error occurrence was related to make safe workplace (evaluation phase with 32.4 % and lowest probability of occurrence error in detection alarm (awareness phase with 1.8 %, probability. The highest severity of error was in the evaluation phase and the lowest severity of error was in the awareness and recovery phase. Maximum risk level was related to the evaluating exit routes and selecting one route and choosy another exit route and minimum risk level was related to the four evaluation phases. . Conclusion: To reduce the risk of reaction in the exit phases of an emergency situation, the following actions are recommended, based on the finding in this study: A periodic evaluation of the exit phase and modifying them if necessary, conducting more maneuvers and analyzing this results along with a sufficient feedback to the employees.
Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics
Zhu, J. Z.; He, Guowei; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved.
CTER—Rapid estimation of CTF parameters with error assessment
Energy Technology Data Exchange (ETDEWEB)
Penczek, Pawel A., E-mail: Pawel.A.Penczek@uth.tmc.edu [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Fang, Jia [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Li, Xueming; Cheng, Yifan [The Keck Advanced Microscopy Laboratory, Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158 (United States); Loerke, Justus; Spahn, Christian M.T. [Institut für Medizinische Physik und Biophysik, Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin (Germany)
2014-05-01
In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300 kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03 Å without, and 3.85 Å with, inclusion of astigmatism parameters. - Highlights: • We describe methodology for estimation of CTF parameters with error assessment. • Error estimates provide means for automated elimination of inferior micrographs. • High computational efficiency allows real-time monitoring of EM data quality. • Accurate CTF estimation yields structure of the 80S human ribosome at 3.85 Å.
Estimation of Branch Topology Errors in Power Networks by WLAN State Estimation
Energy Technology Data Exchange (ETDEWEB)
Kim, Hong Rae [Soonchunhyang University(Korea); Song, Kyung Bin [Kei Myoung University(Korea)
2000-06-01
The purpose of this paper is to detect and identify topological errors in order to maintain a reliable database for the state estimator. In this paper, a two stage estimation procedure is used to identify the topology errors. At the first stage, the WLAV state estimator which has characteristics to remove bad data during the estimation procedure is run for finding out the suspected branches at which topology errors take place. The resulting residuals are normalized and the measurements with significant normalized residuals are selected. A set of suspected branches is formed based on these selected measurements; if the selected measurement if a line flow, the corresponding branch is suspected; if it is an injection, then all the branches connecting the injection bus to its immediate neighbors are suspected. A new WLAV state estimator adding the branch flow errors in the state vector is developed to identify the branch topology errors. Sample cases of single topology error and topology error with a measurement error are applied to IEEE 14 bus test system. (author). 24 refs., 1 fig., 9 tabs.
Exact error estimation for solutions of nuclide chain equations
International Nuclear Information System (INIS)
Tachihara, Hidekazu; Sekimoto, Hiroshi
1999-01-01
The exact solution of nuclide chain equations within arbitrary figures is obtained for a linear chain by employing the Bateman method in the multiple-precision arithmetic. The exact error estimation of major calculation methods for a nuclide chain equation is done by using this exact solution as a standard. The Bateman, finite difference, Runge-Kutta and matrix exponential methods are investigated. The present study confirms the following. The original Bateman method has very low accuracy in some cases, because of large-scale cancellations. The revised Bateman method by Siewers reduces the occurrence of cancellations and thereby shows high accuracy. In the time difference method as the finite difference and Runge-Kutta methods, the solutions are mainly affected by the truncation errors in the early decay time, and afterward by the round-off errors. Even though the variable time mesh is employed to suppress the accumulation of round-off errors, it appears to be nonpractical. Judging from these estimations, the matrix exponential method is the best among all the methods except the Bateman method whose calculation process for a linear chain is not identical with that for a general one. (author)
GPS/DR Error Estimation for Autonomous Vehicle Localization.
Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In
2015-08-21
Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.
GPS/DR Error Estimation for Autonomous Vehicle Localization
Directory of Open Access Journals (Sweden)
Byung-Hyun Lee
2015-08-01
Full Text Available Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.
Regularization and error estimates for nonhomogeneous backward heat problems
Directory of Open Access Journals (Sweden)
Duc Trong Dang
2006-01-01
Full Text Available In this article, we study the inverse time problem for the non-homogeneous heat equation which is a severely ill-posed problem. We regularize this problem using the quasi-reversibility method and then obtain error estimates on the approximate solutions. Solutions are calculated by the contraction principle and shown in numerical experiments. We obtain also rates of convergence to the exact solution.
Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas
2005-01-01
The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.
Hall, Eric Joseph; Hoel, Hå kon; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
2016-01-01
posteriori error estimates fail to capture. We propose goal-oriented estimates, based on local error indicators, for the pathwise Galerkin and expected quadrature errors committed in standard, continuous, piecewise linear finite element approximations
Interpolation Error Estimates for Mean Value Coordinates over Convex Polygons.
Rand, Alexander; Gillette, Andrew; Bajaj, Chandrajit
2013-08-01
In a similar fashion to estimates shown for Harmonic, Wachspress, and Sibson coordinates in [Gillette et al., AiCM, to appear], we prove interpolation error estimates for the mean value coordinates on convex polygons suitable for standard finite element analysis. Our analysis is based on providing a uniform bound on the gradient of the mean value functions for all convex polygons of diameter one satisfying certain simple geometric restrictions. This work makes rigorous an observed practical advantage of the mean value coordinates: unlike Wachspress coordinates, the gradient of the mean value coordinates does not become large as interior angles of the polygon approach π.
Error estimates for discretized quantum stochastic differential inclusions
International Nuclear Information System (INIS)
Ayoola, E.O.
2001-09-01
This paper is concerned with the error estimates involved in the solution of a discrete approximation of a quantum stochastic differential inclusion (QSDI). Our main results rely on certain properties of the averaged modulus of continuity for multivalued sesquilinear forms associated with QSDI. We obtained results concerning the estimates of the Hausdorff distance between the set of solutions of the QSDI and the set of solutions of its discrete approximation. This extend the results of Dontchev and Farkhi concerning classical differential inclusions to the present noncommutative Quantum setting involving inclusions in certain locally convex space. (author)
Classification of resistance to passive motion using minimum probability of error criterion.
Chan, H C; Manry, M T; Kondraske, G V
1987-01-01
Neurologists diagnose many muscular and nerve disorders by classifying the resistance to passive motion of patients' limbs. Over the past several years, a computer-based instrument has been developed for automated measurement and parameterization of this resistance. In the device, a voluntarily relaxed lower extremity is moved at constant velocity by a motorized driver. The torque exerted on the extremity by the machine is sampled, along with the angle of the extremity. In this paper a computerized technique is described for classifying a patient's condition as 'Normal' or 'Parkinson disease' (rigidity), from the torque versus angle curve for the knee joint. A Legendre polynomial, fit to the curve, is used to calculate a set of eight normally distributed features of the curve. The minimum probability of error approach is used to classify the curve as being from a normal or Parkinson disease patient. Data collected from 44 different subjects was processes and the results were compared with an independent physician's subjective assessment of rigidity. There is agreement in better than 95% of the cases, when all of the features are used.
Exact Symbol Error Probability of Cross-QAM in AWGN and Fading Channels
Directory of Open Access Journals (Sweden)
Zhang Xi-chun
2010-01-01
Full Text Available The exact symbol error probability (SEP performance of -ary cross quadrature amplitude modulation (QAM in additive white Gaussian noise (AWGN channel and fading channels, including Rayleigh, Nakagami-m, Rice, and Nakagami-q (Hoyt channels, is analyzed. The obtained closed-form SEP expressions contain a finite (in proportion to sum of single integrals with finite limits and an integrand composed of elementary (exponential, trigonometric, and/or power functions, thus readily enabling numerical evaluation. Particularly, Gaussian -function is a special case of these integrals and is included in the SEP expressions. Simple and very precise approximations, which contain only Gaussian -function for AWGN channel and contain three terms of the single integrals mentioned above for fading channels, respectively, are also given. The analytical expressions show excellent agreement with the simulation results, and numerical evaluation with the proposed expressions reveals that cross QAM can obtain at least 1.1 dB gain compared to rectangular QAM when SEP < 0.3 in all the considered channels.
On estimating probability of presence from use-availability or presence-background data.
Phillips, Steven J; Elith, Jane
2013-06-01
A fundamental ecological modeling task is to estimate the probability that a species is present in (or uses) a site, conditional on environmental variables. For many species, available data consist of "presence" data (locations where the species [or evidence of it] has been observed), together with "background" data, a random sample of available environmental conditions. Recently published papers disagree on whether probability of presence is identifiable from such presence-background data alone. This paper aims to resolve the disagreement, demonstrating that additional information is required. We defined seven simulated species representing various simple shapes of response to environmental variables (constant, linear, convex, unimodal, S-shaped) and ran five logistic model-fitting methods using 1000 presence samples and 10 000 background samples; the simulations were repeated 100 times. The experiment revealed a stark contrast between two groups of methods: those based on a strong assumption that species' true probability of presence exactly matches a given parametric form had highly variable predictions and much larger RMS error than methods that take population prevalence (the fraction of sites in which the species is present) as an additional parameter. For six species, the former group grossly under- or overestimated probability of presence. The cause was not model structure or choice of link function, because all methods were logistic with linear and, where necessary, quadratic terms. Rather, the experiment demonstrates that an estimate of prevalence is not just helpful, but is necessary (except in special cases) for identifying probability of presence. We therefore advise against use of methods that rely on the strong assumption, due to Lele and Keim (recently advocated by Royle et al.) and Lancaster and Imbens. The methods are fragile, and their strong assumption is unlikely to be true in practice. We emphasize, however, that we are not arguing against
A Simulation-Based Soft Error Estimation Methodology for Computer Systems
Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori
2006-01-01
This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...
On estimating the fracture probability of nuclear graphite components
International Nuclear Information System (INIS)
Srinivasan, Makuteswara
2008-01-01
The properties of nuclear grade graphites exhibit anisotropy and could vary considerably within a manufactured block. Graphite strength is affected by the direction of alignment of the constituent coke particles, which is dictated by the forming method, coke particle size, and the size, shape, and orientation distribution of pores in the structure. In this paper, a Weibull failure probability analysis for components is presented using the American Society of Testing Materials strength specification for nuclear grade graphites for core components in advanced high-temperature gas-cooled reactors. The risk of rupture (probability of fracture) and survival probability (reliability) of large graphite blocks are calculated for varying and discrete values of service tensile stresses. The limitations in these calculations are discussed from considerations of actual reactor environmental conditions that could potentially degrade the specification properties because of damage due to complex interactions between irradiation, temperature, stress, and variability in reactor operation
Rigorous covariance propagation of geoid errors to geodetic MDT estimates
Pail, R.; Albertella, A.; Fecher, T.; Savcenko, R.
2012-04-01
The mean dynamic topography (MDT) is defined as the difference between the mean sea surface (MSS) derived from satellite altimetry, averaged over several years, and the static geoid. Assuming geostrophic conditions, from the MDT the ocean surface velocities as important component of global ocean circulation can be derived from it. Due to the availability of GOCE gravity field models, for the very first time MDT can now be derived solely from satellite observations (altimetry and gravity) down to spatial length-scales of 100 km and even below. Global gravity field models, parameterized in terms of spherical harmonic coefficients, are complemented by the full variance-covariance matrix (VCM). Therefore, for the geoid component a realistic statistical error estimate is available, while the error description of the altimetric component is still an open issue and is, if at all, attacked empirically. In this study we make the attempt to perform, based on the full gravity VCM, rigorous error propagation to derived geostrophic surface velocities, thus also considering all correlations. For the definition of the static geoid we use the third release of the time-wise GOCE model, as well as the satellite-only combination model GOCO03S. In detail, we will investigate the velocity errors resulting from the geoid component in dependence of the harmonic degree, and the impact of using/no using covariances on the MDT errors and its correlations. When deriving an MDT, it is spectrally filtered to a certain maximum degree, which is usually driven by the signal content of the geoid model, by applying isotropic or non-isotropic filters. Since this filtering is acting also on the geoid component, the consistent integration of this filter process into the covariance propagation shall be performed, and its impact shall be quantified. The study will be performed for MDT estimates in specific test areas of particular oceanographic interest.
Application of the Unbounded Probability Distribution of the Johnson System for Floods Estimation
Directory of Open Access Journals (Sweden)
Campos-Aranda Daniel Francisco
2015-09-01
Full Text Available Floods designs constitute a key to estimate the sizing of new water works and to review the hydrological security of existing ones. The most reliable method for estimating their magnitudes associated with certain return periods is to fit a probabilistic model to available records of maximum annual flows. Since such model is at first unknown, several models need to be tested in order to select the most appropriate one according to an arbitrary statistical index, commonly the standard error of fit. Several probability distributions have shown versatility and consistency of results when processing floods records and therefore, its application has been established as a norm or precept. The Johnson System has three families of distributions, one of which is the Log–Normal model with three parameters of fit, which is also the border between the bounded distributions and those with no upper limit. These families of distributions have four adjustment parameters and converge to the standard normal distribution, so that their predictions are obtained with such a model. Having contrasted the three probability distributions established by precept in 31 historical records of hydrological events, the Johnson system is applied to such data. The results of the unbounded distribution of the Johnson system (SJU are compared to the optimal results from the three distributions. It was found that the predictions of the SJU distribution are similar to those obtained with the other models in the low return periods ( 1000 years. Because of its theoretical support, the SJU model is recommended in flood estimation.
Directory of Open Access Journals (Sweden)
Nazelie Kassabian
2014-06-01
Full Text Available Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs. This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold.
International Nuclear Information System (INIS)
Embrey, D.E.; Humphreys, P.; Rosa, E.A.; Kirwan, B.; Rea, K.
1984-07-01
This two-volume report presents the procedures and analyses performed in developing an approach for structuring expert judgments to estimate human error probabilities. Volume I presents an overview of work performed in developing the approach: SLIM-MAUD (Success Likelihood Index Methodology, implemented through the use of an interactive computer program called MAUD-Multi-Attribute Utility Decomposition). Volume II provides a more detailed analysis of the technical issues underlying the approach
average probability of failure on demand estimation for burner
African Journals Online (AJOL)
HOD
Pij – Probability from state i to j. 1. INTRODUCTION. In the process .... the numerical value of the PFD as result of components, sub-system ... ignored in probabilistic risk assessment it may lead to ...... Markov chains for a holistic modeling of SIS.
Estimated probability of stroke among medical outpatients in Enugu ...
African Journals Online (AJOL)
Risk factors for stroke were evaluated using a series of laboratory tests, medical history and physical examinations. The 10‑year probability of stroke was determined by applying the Framingham stroke risk equation. Statistical analysis was performed with the use of the SPSS 17.0 software package (SPSS Inc., Chicago, IL, ...
Estimating Recovery Failure Probabilities in Off-normal Situations from Full-Scope Simulator Data
Energy Technology Data Exchange (ETDEWEB)
Kim, Yochan; Park, Jinkyun; Kim, Seunghwan; Choi, Sun Yeong; Jung, Wondea [Korea Atomic Research Institute, Daejeon (Korea, Republic of)
2016-10-15
As part of this effort, KAERI developed the Human Reliability data EXtraction (HuREX) framework and is collecting full-scope simulator-based human reliability data into the OPERA (Operator PErformance and Reliability Analysis) database. In this study, with the series of estimation research for HEPs or PSF effects, significant information for a quantitative HRA analysis, recovery failure probabilities (RFPs), were produced from the OPERA database. Unsafe acts can occur at any time in safety-critical systems and the operators often manage the systems by discovering their errors and eliminating or mitigating them. To model the recovery processes or recovery strategies, there were several researches that categorize the recovery behaviors. Because the recent human error trends are required to be considered during a human reliability analysis, Jang et al. can be seen as an essential effort of the data collection. However, since the empirical results regarding soft controls were produced from a controlled laboratory environment with student participants, it is necessary to analyze a wide range of operator behaviors using full-scope simulators. This paper presents the statistics related with human error recovery behaviors obtained from the full-scope simulations that in-site operators participated in. In this study, the recovery effects by shift changes or technical support centers were not considered owing to a lack of simulation data.
Normalized Minimum Error Entropy Algorithm with Recursive Power Estimation
Directory of Open Access Journals (Sweden)
Namyong Kim
2016-06-01
Full Text Available The minimum error entropy (MEE algorithm is known to be superior in signal processing applications under impulsive noise. In this paper, based on the analysis of behavior of the optimum weight and the properties of robustness against impulsive noise, a normalized version of the MEE algorithm is proposed. The step size of the MEE algorithm is normalized with the power of input entropy that is estimated recursively for reducing its computational complexity. The proposed algorithm yields lower minimum MSE (mean squared error and faster convergence speed simultaneously than the original MEE algorithm does in the equalization simulation. On the condition of the same convergence speed, its performance enhancement in steady state MSE is above 3 dB.
Naive Probability: Model-based Estimates of Unique Events
2014-05-04
of inference. Argument and Computation, 1–17, iFirst. Khemlani, S., & Johnson-Laird, P.N. (2012b). Theories of the syllogism: A meta -analysis...is the probability that… 1 space tourism will achieve widespread popularity in the next 50 years? advances in material science will lead to the... governments dedicate more resources to contacting extra-terrestrials? 8 the United States adopts an open border policy of universal acceptance? English is
Estimating the Probability of Wind Ramping Events: A Data-driven Approach
Wang, Cheng; Wei, Wei; Wang, Jianhui; Qiu, Feng
2016-01-01
This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.
Estimating the concordance probability in a survival analysis with a discrete number of risk groups.
Heller, Glenn; Mo, Qianxing
2016-04-01
A clinical risk classification system is an important component of a treatment decision algorithm. A measure used to assess the strength of a risk classification system is discrimination, and when the outcome is survival time, the most commonly applied global measure of discrimination is the concordance probability. The concordance probability represents the pairwise probability of lower patient risk given longer survival time. The c-index and the concordance probability estimate have been used to estimate the concordance probability when patient-specific risk scores are continuous. In the current paper, the concordance probability estimate and an inverse probability censoring weighted c-index are modified to account for discrete risk scores. Simulations are generated to assess the finite sample properties of the concordance probability estimate and the weighted c-index. An application of these measures of discriminatory power to a metastatic prostate cancer risk classification system is examined.
Improved Variable Window Kernel Estimates of Probability Densities
Hall, Peter; Hu, Tien Chung; Marron, J. S.
1995-01-01
Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher-order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Terrell and Scott show that these results ca...
A Posteriori Error Estimates Including Algebraic Error and Stopping Criteria for Iterative Solvers
Czech Academy of Sciences Publication Activity Database
Jiránek, P.; Strakoš, Zdeněk; Vohralík, M.
2010-01-01
Roč. 32, č. 3 (2010), s. 1567-1590 ISSN 1064-8275 R&D Projects: GA AV ČR IAA100300802 Grant - others:GA ČR(CZ) GP201/09/P464 Institutional research plan: CEZ:AV0Z10300504 Keywords : second-order elliptic partial differential equation * finite volume method * a posteriori error estimates * iterative methods for linear algebraic systems * conjugate gradient method * stopping criteria Subject RIV: BA - General Mathematics Impact factor: 3.016, year: 2010
Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters
Hoshino, Takahiro; Shigemasu, Kazuo
2008-01-01
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Sharp probability estimates for Shor's order-finding algorithm
Bourdon, P. S.; Williams, H. T.
2006-01-01
Let N be a (large positive integer, let b > 1 be an integer relatively prime to N, and let r be the order of b modulo N. Finally, let QC be a quantum computer whose input register has the size specified in Shor's original description of his order-finding algorithm. We prove that when Shor's algorithm is implemented on QC, then the probability P of obtaining a (nontrivial) divisor of r exceeds 0.7 whenever N exceeds 2^{11}-1 and r exceeds 39, and we establish that 0.7736 is an asymptotic lower...
Estimated Probability of a Cervical Spine Injury During an ISS Mission
Brooker, John E.; Weaver, Aaron S.; Myers, Jerry G.
2013-01-01
Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a
Smoothed Spectra, Ogives, and Error Estimates for Atmospheric Turbulence Data
Dias, Nelson Luís
2018-01-01
A systematic evaluation is conducted of the smoothed spectrum, which is a spectral estimate obtained by averaging over a window of contiguous frequencies. The technique is extended to the ogive, as well as to the cross-spectrum. It is shown that, combined with existing variance estimates for the periodogram, the variance—and therefore the random error—associated with these estimates can be calculated in a straightforward way. The smoothed spectra and ogives are biased estimates; with simple power-law analytical models, correction procedures are devised, as well as a global constraint that enforces Parseval's identity. Several new results are thus obtained: (1) The analytical variance estimates compare well with the sample variance calculated for the Bartlett spectrum and the variance of the inertial subrange of the cospectrum is shown to be relatively much larger than that of the spectrum. (2) Ogives and spectra estimates with reduced bias are calculated. (3) The bias of the smoothed spectrum and ogive is shown to be negligible at the higher frequencies. (4) The ogives and spectra thus calculated have better frequency resolution than the Bartlett spectrum, with (5) gradually increasing variance and relative error towards the low frequencies. (6) Power-law identification and extraction of the rate of dissipation of turbulence kinetic energy are possible directly from the ogive. (7) The smoothed cross-spectrum is a valid inner product and therefore an acceptable candidate for coherence and spectral correlation coefficient estimation by means of the Cauchy-Schwarz inequality. The quadrature, phase function, coherence function and spectral correlation function obtained from the smoothed spectral estimates compare well with the classical ones derived from the Bartlett spectrum.
Development of a framework to estimate human error for diagnosis tasks in advanced control room
International Nuclear Information System (INIS)
Kim, Ar Ryum; Jang, In Seok; Seong, Proong Hyun
2014-01-01
In the emergency situation of nuclear power plants (NPPs), a diagnosis of the occurring events is crucial for managing or controlling the plant to a safe and stable condition. If the operators fail to diagnose the occurring events or relevant situations, their responses can eventually inappropriate or inadequate Accordingly, huge researches have been performed to identify the cause of diagnosis error and estimate the probability of diagnosis error. D.I Gertman et al. asserted that 'the cognitive failures stem from erroneous decision-making, poor understanding of rules and procedures, and inadequate problem solving and this failures may be due to quality of data and people's capacity for processing information'. Also many researchers have asserted that human-system interface (HSI), procedure, training and available time are critical factors to cause diagnosis error. In nuclear power plants, a diagnosis of the event is critical for safe condition of the system. As advanced main control room is being adopted in nuclear power plants, the operators may obtain the plant data via computer-based HSI and procedure. Also many researchers have asserted that HSI, procedure, training and available time are critical factors to cause diagnosis error. In this regards, using simulation data, diagnosis errors and its causes were identified. From this study, some useful insights to reduce diagnosis errors of operators in advanced main control room were provided
Are Low-order Covariance Estimates Useful in Error Analyses?
Baker, D. F.; Schimel, D.
2005-12-01
Atmospheric trace gas inversions, using modeled atmospheric transport to infer surface sources and sinks from measured concentrations, are most commonly done using least-squares techniques that return not only an estimate of the state (the surface fluxes) but also the covariance matrix describing the uncertainty in that estimate. Besides allowing one to place error bars around the estimate, the covariance matrix may be used in simulation studies to learn what uncertainties would be expected from various hypothetical observing strategies. This error analysis capability is routinely used in designing instrumentation, measurement campaigns, and satellite observing strategies. For example, Rayner, et al (2002) examined the ability of satellite-based column-integrated CO2 measurements to constrain monthly-average CO2 fluxes for about 100 emission regions using this approach. Exact solutions for both state vector and covariance matrix become computationally infeasible, however, when the surface fluxes are solved at finer resolution (e.g., daily in time, under 500 km in space). It is precisely at these finer scales, however, that one would hope to be able to estimate fluxes using high-density satellite measurements. Non-exact estimation methods such as variational data assimilation or the ensemble Kalman filter could be used, but they achieve their computational savings by obtaining an only approximate state estimate and a low-order approximation of the true covariance. One would like to be able to use this covariance matrix to do the same sort of error analyses as are done with the full-rank covariance, but is it correct to do so? Here we compare uncertainties and `information content' derived from full-rank covariance matrices obtained from a direct, batch least squares inversion to those from the incomplete-rank covariance matrices given by a variational data assimilation approach solved with a variable metric minimization technique (the Broyden-Fletcher- Goldfarb
On Bit Error Probability and Power Optimization in Multihop Millimeter Wave Relay Systems
Chelli, Ali
2018-01-15
5G networks are expected to provide gigabit data rate to users via millimeter-wave (mmWave) communication technology. One of the major problem faced by mmWaves is that they cannot penetrate buildings. In this paper, we utilize multihop relaying to overcome the signal blockage problem in mmWave band. The multihop relay network comprises a source device, several relay devices and a destination device and uses device-todevice communication. Relay devices redirect the source signal to avoid the obstacles existing in the propagation environment. Each device amplifies and forwards the signal to the next device, such that a multihop link ensures the connectivity between the source device and the destination device. We consider that the relay devices and the destination device are affected by external interference and investigate the bit error probability (BEP) of this multihop mmWave system. Note that the study of the BEP allows quantifying the quality of communication and identifying the impact of different parameters on the system reliability. In this way, the system parameters, such as the powers allocated to different devices, can be tuned to maximize the link reliability. We derive exact expressions for the BEP of M-ary quadrature amplitude modulation (M-QAM) and M-ary phase-shift keying (M-PSK) in terms of multivariate Meijer’s G-function. Due to the complicated expression of the exact BEP, a tight lower-bound expression for the BEP is derived using a novel Mellin-approach. Moreover, an asymptotic expression for the BEP at high SIR regime is derived and used to determine the diversity and the coding gain of the system. Additionally, we optimize the power allocation at different devices subject to a sum power constraint such that the BEP is minimized. Our analysis reveals that optimal power allocation allows achieving more than 3 dB gain compared to the equal power allocation.This research work can serve as a framework for designing and optimizing mmWave multihop
International Nuclear Information System (INIS)
Fruehwirth, R.
1993-01-01
We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)
Percentile estimation using the normal and lognormal probability distribution
International Nuclear Information System (INIS)
Bement, T.R.
1980-01-01
Implicitly or explicitly percentile estimation is an important aspect of the analysis of aerial radiometric survey data. Standard deviation maps are produced for quadrangles which are surveyed as part of the National Uranium Resource Evaluation. These maps show where variables differ from their mean values by more than one, two or three standard deviations. Data may or may not be log-transformed prior to analysis. These maps have specific percentile interpretations only when proper distributional assumptions are met. Monte Carlo results are presented in this paper which show the consequences of estimating percentiles by: (1) assuming normality when the data are really from a lognormal distribution; and (2) assuming lognormality when the data are really from a normal distribution
METAPHOR: Probability density estimation for machine learning based photometric redshifts
Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-06-01
We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).
Fusion probability and survivability in estimates of heaviest nuclei production
International Nuclear Information System (INIS)
Sagaidak, Roman
2012-01-01
A number of theoretical models have been recently developed to predict production cross sections for the heaviest nuclei in fusion-evaporation reactions. All the models reproduce cross sections obtained in experiments quite well. At the same time they give fusion probability values P fus ≡ P CN differed within several orders of the value. This difference implies a corresponding distinction in the calculated values of survivability. The production of the heaviest nuclei (from Cm to the region of superheavy elements (SHE) close to Z = 114 and N = 184) in fusion-evaporation reactions induced by heavy ions has been considered in a systematic way within the framework of the barrier-passing (fusion) model coupled with the standard statistical model (SSM) of the compound nucleus (CN) decay. Both models are incorporated into the HIVAP code. Available data on the excitation functions for fission and evaporation residues (ER) produced in very asymmetric combinations can be described rather well within the framework of HIVAP. Cross-section data obtained in these reactions allow one to choose model parameters quite definitely. Thus one can scale and fix macroscopic (liquid-drop) fission barriers for nuclei involved in the evaporation-fission cascade. In less asymmetric combinations (with 22 Ne and heavier projectiles) effects of fusion suppression caused by quasi-fission are starting to appear in the entrance channel of reactions. The P fus values derived from the capture-fission and fusion-fission cross-sections obtained at energies above the Bass barrier were plotted as a function of the Coulomb parameter. For more symmetric combinations one can deduce the P fus values semi-empirically, using the ER and fission excitation functions measured in experiments, and applying SSM model with parameters obtained in the analysis of a very asymmetric combination leading to the production of (nearly) the same CN, as was done for reactions leading to the pre-actinide nuclei formation
Estimation of post-test probabilities by residents: Bayesian reasoning versus heuristics?
Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P; Ghali, William; Wright, Bruce; McLaughlin, Kevin
2014-08-01
Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of disease probability estimates. In this study our objective was to explore whether Internal Medicine residents use a Bayesian process to estimate disease probabilities by comparing their disease probability estimates to literature-derived Bayesian post-test probabilities. We gave 35 Internal Medicine residents four clinical vignettes in the form of a referral letter and asked them to estimate the post-test probability of the target condition in each case. We then compared these to literature-derived probabilities. For each vignette the estimated probability was significantly different from the literature-derived probability. For the two cases with low literature-derived probability our participants significantly overestimated the probability of these target conditions being the correct diagnosis, whereas for the two cases with high literature-derived probability the estimated probability was significantly lower than the calculated value. Our results suggest that residents generate inaccurate post-test probability estimates. Possible explanations for this include ineffective application of Bayesian reasoning, attribute substitution whereby a complex cognitive task is replaced by an easier one (e.g., a heuristic), or systematic rater bias, such as central tendency bias. Further studies are needed to identify the reasons for inaccuracy of disease probability estimates and to explore ways of improving accuracy.
Fusion probability and survivability in estimates of heaviest nuclei production
Directory of Open Access Journals (Sweden)
Sagaidak Roman N.
2012-02-01
Full Text Available Production of the heavy and heaviest nuclei (from Po to the region of superheavy elements close to Z=114 and N=184 in fusion-evaporation reactions induced by heavy ions has been considered in a systematic way within the framework of the barrier-passing model coupled with the statistical model (SM of de-excitation of a compound nucleus (CN. Excitation functions for fission and evaporation residues (ER measured in very asymmetric combinations can be described rather well. One can scale and fix macroscopic (liquid-drop fission barriers for nuclei involved in the calculation of survivability with SM. In less asymmetric combinations, effects of fusion suppression caused by quasi-fission (QF are starting to appear in the entrance channel of reactions. QF effects could be semi-empirically taken into account using fusion probabilities deduced as the ratio of measured ER cross sections to the ones obtained in the assumption of absence of the fusion suppression in corresponding reactions. SM parameters (fission barriers obtained at the analysis of a very asymmetric combination leading to the production of (nearly the same CN should be used for this evaluation.
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Liu, W. F.
2013-01-01
Estimation of extreme response and failure probability of structures subjected to ultimate design loads is essential for structural design of wind turbines according to the new standard IEC61400-1. This task is focused on in the present paper in virtue of probability density evolution method (PDEM......), which underlies the schemes of random vibration analysis and structural reliability assessment. The short-term rare failure probability of 5-mega-watt wind turbines, for illustrative purposes, in case of given mean wind speeds and turbulence levels is investigated through the scheme of extreme value...... distribution instead of any other approximate schemes of fitted distribution currently used in statistical extrapolation techniques. Besides, the comparative studies against the classical fitted distributions and the standard Monte Carlo techniques are carried out. Numerical results indicate that PDEM exhibits...
Fast Outage Probability Simulation for FSO Links with a Generalized Pointing Error Model
Ben Issaid, Chaouki; Park, Kihong; Alouini, Mohamed-Slim; Tempone, Raul
2017-01-01
Over the past few years, free-space optical (FSO) communication has gained significant attention. In fact, FSO can provide cost-effective and unlicensed links, with high-bandwidth capacity and low error rate, making it an exciting alternative
Use of probabilistic methods for estimating failure probabilities and directing ISI-efforts
Energy Technology Data Exchange (ETDEWEB)
Nilsson, F; Brickstad, B [University of Uppsala, (Switzerland)
1988-12-31
Some general aspects of the role of Non Destructive Testing (NDT) efforts on the resulting probability of core damage is discussed. A simple model for the estimation of the pipe break probability due to IGSCC is discussed. It is partly based on analytical procedures, partly on service experience from the Swedish BWR program. Estimates of the break probabilities indicate that further studies are urgently needed. It is found that the uncertainties about the initial crack configuration are large contributors to the total uncertainty. Some effects of the inservice inspection are studied and it is found that the detection probabilities influence the failure probabilities. (authors).
Error estimation for CFD aeroheating prediction under rarefied flow condition
Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian
2014-12-01
Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.
Estimating deficit probabilities with price-responsive demand in contract-based electricity markets
International Nuclear Information System (INIS)
Galetovic, Alexander; Munoz, Cristian M.
2009-01-01
Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower
Influence of binary mask estimation errors on robust speaker identification
DEFF Research Database (Denmark)
May, Tobias
2017-01-01
Missing-data strategies have been developed to improve the noise-robustness of automatic speech recognition systems in adverse acoustic conditions. This is achieved by classifying time-frequency (T-F) units into reliable and unreliable components, as indicated by a so-called binary mask. Different...... approaches have been proposed to handle unreliable feature components, each with distinct advantages. The direct masking (DM) approach attenuates unreliable T-F units in the spectral domain, which allows the extraction of conventionally used mel-frequency cepstral coefficients (MFCCs). Instead of attenuating....... Since each of these approaches utilizes the knowledge about reliable and unreliable feature components in a different way, they will respond differently to estimation errors in the binary mask. The goal of this study was to identify the most effective strategy to exploit knowledge about reliable...
Estimation and asymptotic theory for transition probabilities in Markov Renewal Multi–state models
Spitoni, C.; Verduijn, M.; Putter, H.
2012-01-01
In this paper we discuss estimation of transition probabilities for semi–Markov multi–state models. Non–parametric and semi–parametric estimators of the transition probabilities for a large class of models (forward going models) are proposed. Large sample theory is derived using the functional
International Nuclear Information System (INIS)
Eedy, W.; Hart, D.
1988-05-01
The risk to human health from radioactive waste management sites can be calculated as the product of the probability of accidental exposure (intrusion) times the probability of a health effect from such exposure. This report reviews the literature and evaluates methods used to predict the probabilities for unintentional intrusion into radioactive waste management areas in Canada over a 10,000-year period. Methods to predict such probabilities are available. They generally assume a long-term stability in terms of existing resource uses and society in the management area. The major potential for errors results from the unlikeliness of these assumptions holding true over such lengthy periods of prediction
Yang, Liang
2013-04-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation error and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use these expressions to evaluate the outage probability and error probability. Numerical results show that the approximate closed-form expressions are very close to the exact ones. © 2013 IEEE.
Schillaci, Michael A; Schillaci, Mario E
2009-02-01
The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (nresearchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.
International Nuclear Information System (INIS)
Varde, P. V.; Lee, D. Y.; Han, J. B.
2003-03-01
A case of study on human reliability analysis has been performed as part of reliability analysis of digital protection system of the reactor automatically actuates the shutdown system of the reactor when demanded. However, the safety analysis takes credit for operator action as a diverse mean for tripping the reactor for, though a low probability, ATWS scenario. Based on the available information two cases, viz., human error in tripping the reactor and calibration error for instrumentations in protection system, have been analyzed. Wherever applicable a parametric study has also been performed
CTER-rapid estimation of CTF parameters with error assessment.
Penczek, Pawel A; Fang, Jia; Li, Xueming; Cheng, Yifan; Loerke, Justus; Spahn, Christian M T
2014-05-01
In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03Å without, and 3.85Å with, inclusion of astigmatism parameters. Copyright © 2014 Elsevier B.V. All rights reserved.
Results and Error Estimates from GRACE Forward Modeling over Antarctica
Bonin, Jennifer; Chambers, Don
2013-04-01
Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Antarctica. However when tested previously, the least squares technique has required constraints in the form of added process noise in order to be reliable. Poor choice of local basin layout has also adversely affected results, as has the choice of spatial smoothing used with GRACE. To develop design parameters which will result in correct high-resolution mass detection and to estimate the systematic errors of the method over Antarctica, we use a "truth" simulation of the Antarctic signal. We apply the optimal parameters found from the simulation to RL05 GRACE data across Antarctica and the surrounding ocean. We particularly focus on separating the Antarctic peninsula's mass signal from that of the rest of western Antarctica. Additionally, we characterize how well the technique works for removing land leakage signal from the nearby ocean, particularly that near the Drake Passage.
Black hole spectroscopy: Systematic errors and ringdown energy estimates
Baibhav, Vishal; Berti, Emanuele; Cardoso, Vitor; Khanna, Gaurav
2018-02-01
The relaxation of a distorted black hole to its final state provides important tests of general relativity within the reach of current and upcoming gravitational wave facilities. In black hole perturbation theory, this phase consists of a simple linear superposition of exponentially damped sinusoids (the quasinormal modes) and of a power-law tail. How many quasinormal modes are necessary to describe waveforms with a prescribed precision? What error do we incur by only including quasinormal modes, and not tails? What other systematic effects are present in current state-of-the-art numerical waveforms? These issues, which are basic to testing fundamental physics with distorted black holes, have hardly been addressed in the literature. We use numerical relativity waveforms and accurate evolutions within black hole perturbation theory to provide some answers. We show that (i) a determination of the fundamental l =m =2 quasinormal frequencies and damping times to within 1% or better requires the inclusion of at least the first overtone, and preferably of the first two or three overtones; (ii) a determination of the black hole mass and spin with precision better than 1% requires the inclusion of at least two quasinormal modes for any given angular harmonic mode (ℓ , m ). We also improve on previous estimates and fits for the ringdown energy radiated in the various multipoles. These results are important to quantify theoretical (as opposed to instrumental) limits in parameter estimation accuracy and tests of general relativity allowed by ringdown measurements with high signal-to-noise ratio gravitational wave detectors.
Directory of Open Access Journals (Sweden)
Zhanshan Wang
2014-01-01
Full Text Available The control of a high performance alternative current (AC motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM. In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.
Bias and spread in extreme value theory measurements of probability of error
Smith, J. G.
1972-01-01
Extreme value theory is examined to explain the cause of the bias and spread in performance of communications systems characterized by low bit rates and high data reliability requirements, for cases in which underlying noise is Gaussian or perturbed Gaussian. Experimental verification is presented and procedures that minimize these effects are suggested. Even under these conditions, however, extreme value theory test results are not particularly more significant than bit error rate tests.
International Nuclear Information System (INIS)
Jang, Inseok; Kim, Ar Ryum; Harbi, Mohamed Ali Salem Al; Lee, Seung Jun; Kang, Hyun Gook; Seong, Poong Hyun
2013-01-01
Highlights: ► The operation environment of MCRs in NPPs has changed by adopting new HSIs. ► The operation action in NPP Advanced MCRs is performed by soft control. ► Different basic human error probabilities (BHEPs) should be considered. ► BHEPs in a soft control operation environment are investigated empirically. ► This work will be helpful to verify if soft control has positive or negative effects. -- Abstract: By adopting new human–system interfaces that are based on computer-based technologies, the operation environment of main control rooms (MCRs) in nuclear power plants (NPPs) has changed. The MCRs that include these digital and computer technologies, such as large display panels, computerized procedures, soft controls, and so on, are called Advanced MCRs. Among the many features in Advanced MCRs, soft controls are an important feature because the operation action in NPP Advanced MCRs is performed by soft control. Using soft controls such as mouse control, touch screens, and so on, operators can select a specific screen, then choose the controller, and finally manipulate the devices. However, because of the different interfaces between soft control and hardwired conventional type control, different basic human error probabilities (BHEPs) should be considered in the Human Reliability Analysis (HRA) for advanced MCRs. Although there are many HRA methods to assess human reliabilities, such as Technique for Human Error Rate Prediction (THERP), Accident Sequence Evaluation Program (ASEP), Human Error Assessment and Reduction Technique (HEART), Human Event Repository and Analysis (HERA), Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR), Cognitive Reliability and Error Analysis Method (CREAM), and so on, these methods have been applied to conventional MCRs, and they do not consider the new features of advance MCRs such as soft controls. As a result, there is an insufficient database for assessing human reliabilities in advanced
Estimating the probability that the Taser directly causes human ventricular fibrillation.
Sun, H; Haemmerich, D; Rahko, P S; Webster, J G
2010-04-01
This paper describes the first methodology and results for estimating the order of probability for Tasers directly causing human ventricular fibrillation (VF). The probability of an X26 Taser causing human VF was estimated using: (1) current density near the human heart estimated by using 3D finite-element (FE) models; (2) prior data of the maximum dart-to-heart distances that caused VF in pigs; (3) minimum skin-to-heart distances measured in erect humans by echocardiography; and (4) dart landing distribution estimated from police reports. The estimated mean probability of human VF was 0.001 for data from a pig having a chest wall resected to the ribs and 0.000006 for data from a pig with no resection when inserting a blunt probe. The VF probability for a given dart location decreased with the dart-to-heart horizontal distance (radius) on the skin surface.
A Scheduling Algorithm for Minimizing the Packet Error Probability in Clusterized TDMA Networks
Directory of Open Access Journals (Sweden)
Arash T. Toyserkani
2009-01-01
Full Text Available We consider clustered wireless networks, where transceivers in a cluster use a time-slotted mechanism (TDMA to access a wireless channel that is shared among several clusters. An approximate expression for the packet-loss probability is derived for networks with one or more mutually interfering clusters in Rayleigh fading environments, and the approximation is shown to be good for relevant scenarios. We then present a scheduling algorithm, based on Lagrangian duality, that exploits the derived packet-loss model in an attempt to minimize the average packet-loss probability in the network. Computer simulations of the proposed scheduling algorithm show that a significant increase in network throughput can be achieved compared to uncoordinated scheduling. Empirical trials also indicate that the proposed optimization algorithm almost always converges to an optimal schedule with a reasonable number of iterations. Thus, the proposed algorithm can also be used for bench-marking suboptimal scheduling algorithms.
Measurement Error Estimation for Capacitive Voltage Transformer by Insulation Parameters
Directory of Open Access Journals (Sweden)
Bin Chen
2017-03-01
Full Text Available Measurement errors of a capacitive voltage transformer (CVT are relevant to its equivalent parameters for which its capacitive divider contributes the most. In daily operation, dielectric aging, moisture, dielectric breakdown, etc., it will exert mixing effects on a capacitive divider’s insulation characteristics, leading to fluctuation in equivalent parameters which result in the measurement error. This paper proposes an equivalent circuit model to represent a CVT which incorporates insulation characteristics of a capacitive divider. After software simulation and laboratory experiments, the relationship between measurement errors and insulation parameters is obtained. It indicates that variation of insulation parameters in a CVT will cause a reasonable measurement error. From field tests and calculation, equivalent capacitance mainly affects magnitude error, while dielectric loss mainly affects phase error. As capacitance changes 0.2%, magnitude error can reach −0.2%. As dielectric loss factor changes 0.2%, phase error can reach 5′. An increase of equivalent capacitance and dielectric loss factor in the high-voltage capacitor will cause a positive real power measurement error. An increase of equivalent capacitance and dielectric loss factor in the low-voltage capacitor will cause a negative real power measurement error.
Estimation of functional failure probability of passive systems based on subset simulation method
International Nuclear Information System (INIS)
Wang Dongqing; Wang Baosheng; Zhang Jianmin; Jiang Jing
2012-01-01
In order to solve the problem of multi-dimensional epistemic uncertainties and small functional failure probability of passive systems, an innovative reliability analysis algorithm called subset simulation based on Markov chain Monte Carlo was presented. The method is found on the idea that a small failure probability can be expressed as a product of larger conditional failure probabilities by introducing a proper choice of intermediate failure events. Markov chain Monte Carlo simulation was implemented to efficiently generate conditional samples for estimating the conditional failure probabilities. Taking the AP1000 passive residual heat removal system, for example, the uncertainties related to the model of a passive system and the numerical values of its input parameters were considered in this paper. And then the probability of functional failure was estimated with subset simulation method. The numerical results demonstrate that subset simulation method has the high computing efficiency and excellent computing accuracy compared with traditional probability analysis methods. (authors)
International Nuclear Information System (INIS)
Acquaviva, Viviana; Raichoor, Anand; Gawiser, Eric
2015-01-01
We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties in the photometric redshifts are estimated correctly, so are those on the other SED fitting parameters, such as stellar mass, stellar age, and dust reddening. Furthermore, we find that if the redshift uncertainties are over(under)-estimated, the uncertainties in SED parameters tend to be over(under)-estimated by similar amounts. These results hold even in the presence of severe systematics and provide, for the first time, a mechanism to validate the uncertainties on these parameters via comparison with spectroscopic redshifts. We propose a new technique (annealing) to re-calibrate the joint uncertainties in the photo-z and SED fitting parameters without compromising the performance of the SED fitting + photo-z estimation. This procedure provides a consistent estimation of the multi-dimensional probability distribution function in SED fitting + z parameter space, including all correlations. While the performance of joint SED fitting and photo-z estimation might be hindered by template incompleteness, we demonstrate that the latter is “flagged” by a large fraction of outliers in redshift, and that significant improvements can be achieved by using flexible stellar populations synthesis models and more realistic star formation histories. In all cases, we find that the median stellar age is better recovered than the time elapsed from the onset of star formation. Finally, we show that using a photometric redshift code such as EAZY to obtain redshift probability distributions that are then used as priors for SED fitting codes leads to only a modest bias in the SED fitting parameters and is thus a viable alternative to the simultaneous estimation of SED parameters and photometric redshifts
Estimating the Probability of Traditional Copying, Conditional on Answer-Copying Statistics.
Allen, Jeff; Ghattas, Andrew
2016-06-01
Statistics for detecting copying on multiple-choice tests produce p values measuring the probability of a value at least as large as that observed, under the null hypothesis of no copying. The posterior probability of copying is arguably more relevant than the p value, but cannot be derived from Bayes' theorem unless the population probability of copying and probability distribution of the answer-copying statistic under copying are known. In this article, the authors develop an estimator for the posterior probability of copying that is based on estimable quantities and can be used with any answer-copying statistic. The performance of the estimator is evaluated via simulation, and the authors demonstrate how to apply the formula using actual data. Potential uses, generalizability to other types of cheating, and limitations of the approach are discussed.
Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas
2014-07-01
Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
International Nuclear Information System (INIS)
Kobayashi, H.; Matsunaga, T.; Hoyano, A.
2002-01-01
Absorbed photosynthetically active radiation (APAR), which is defined as downward solar radiation in 400-700 nm absorbed by vegetation, is one of the significant variables for Net Primary Production (NPP) estimation from satellite data. Toward the reduction of the uncertainties in the global NPP estimation, it is necessary to clarify the APAR accuracy. In this paper, first we proposed the improved PAR estimation method based on Eck and Dye's method in which the ultraviolet (UV) reflectivity data derived from Total Ozone Mapping Spectrometer (TOMS) at the top of atmosphere were used for clouds transmittance estimation. The proposed method considered the variable effects of land surface UV reflectivity on the satellite-observed UV data. Monthly mean PAR comparisons between satellite-derived and ground-based data at various meteorological stations in Japan indicated that the improved PAR estimation method reduced the bias errors in the summer season. Assuming the relative error of the fraction of PAR (FPAR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to be 10%, we estimated APAR relative errors to be 10-15%. Annual NPP is calculated using APAR derived from MODIS/ FPAR and the improved PAR estimation method. It is shown that random and bias errors of annual NPP in a 1 km resolution pixel are less than 4% and 6% respectively. The APAR bias errors due to the PAR bias errors also affect the estimated total NPP. We estimated the most probable total annual NPP in Japan by subtracting the bias PAR errors. It amounts about 248 MtC/yr. Using the improved PAR estimation method, and Eck and Dye's method, total annual NPP is 4% and 9% difference from most probable value respectively. The previous intercomparison study among using fifteen NPP models4) showed that global NPP estimations among NPP models are 44.4-66.3 GtC/yr (coefficient of variation = 14%). Hence we conclude that the NPP estimation uncertainty due to APAR estimation error is small
International Nuclear Information System (INIS)
El-Shanshoury, Gh.I.
2015-01-01
Assessing the adequacy of probability distributions for estimating the extreme events of air temperature in Dabaa region is one of the pre-requisite s for any design purpose at Dabaa site which can be achieved by probability approach. In the present study, three extreme value distributions are considered and compared to estimate the extreme events of monthly and annual maximum and minimum temperature. These distributions include the Gumbel/Frechet distributions for estimating the extreme maximum values and Gumbel /Weibull distributions for estimating the extreme minimum values. Lieblein technique and Method of Moments are applied for estimating the distribution para meters. Subsequently, the required design values with a given return period of exceedance are obtained. Goodness-of-Fit tests involving Kolmogorov-Smirnov and Anderson-Darling are used for checking the adequacy of fitting the method/distribution for the estimation of maximum/minimum temperature. Mean Absolute Relative Deviation, Root Mean Square Error and Relative Mean Square Deviation are calculated, as the performance indicators, to judge which distribution and method of parameters estimation are the most appropriate one to estimate the extreme temperatures. The present study indicated that the Weibull distribution combined with Method of Moment estimators gives the highest fit, most reliable, accurate predictions for estimating the extreme monthly and annual minimum temperature. The Gumbel distribution combined with Method of Moment estimators showed the highest fit, accurate predictions for the estimation of the extreme monthly and annual maximum temperature except for July, August, October and November. The study shows that the combination of Frechet distribution with Method of Moment is the most accurate for estimating the extreme maximum temperature in July, August and November months while t he Gumbel distribution and Lieblein technique is the best for October
Real-time minimal-bit-error probability decoding of convolutional codes
Lee, L.-N.
1974-01-01
A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.
Real-time minimal bit error probability decoding of convolutional codes
Lee, L. N.
1973-01-01
A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.
Estimating Bird / Aircraft Collision Probabilities and Risk Utilizing Spatial Poisson Processes
2012-06-10
ESTIMATING BIRD/AIRCRAFT COLLISION PROBABILITIES AND RISK UTILIZING SPATIAL POISSON PROCESSES GRADUATE...AND RISK UTILIZING SPATIAL POISSON PROCESSES GRADUATE RESEARCH PAPER Presented to the Faculty Department of Operational Sciences...COLLISION PROBABILITIES AND RISK UTILIZING SPATIAL POISSON PROCESSES Brady J. Vaira, BS, MS Major, USAF Approved
A Posteriori Error Estimation for Finite Element Methods and Iterative Linear Solvers
Energy Technology Data Exchange (ETDEWEB)
Melboe, Hallgeir
2001-10-01
This thesis addresses a posteriori error estimation for finite element methods and iterative linear solvers. Adaptive finite element methods have gained a lot of popularity over the last decades due to their ability to produce accurate results with limited computer power. In these methods a posteriori error estimates play an essential role. Not only do they give information about how large the total error is, they also indicate which parts of the computational domain should be given a more sophisticated treatment in order to reduce the error. A posteriori error estimates are traditionally aimed at estimating the global error, but more recently so called goal oriented error estimators have been shown a lot of interest. The name reflects the fact that they estimate the error in user-defined local quantities. In this thesis the main focus is on global error estimators for highly stretched grids and goal oriented error estimators for flow problems on regular grids. Numerical methods for partial differential equations, such as finite element methods and other similar techniques, typically result in a linear system of equations that needs to be solved. Usually such systems are solved using some iterative procedure which due to a finite number of iterations introduces an additional error. Most such algorithms apply the residual in the stopping criterion, whereas the control of the actual error may be rather poor. A secondary focus in this thesis is on estimating the errors that are introduced during this last part of the solution procedure. The thesis contains new theoretical results regarding the behaviour of some well known, and a few new, a posteriori error estimators for finite element methods on anisotropic grids. Further, a goal oriented strategy for the computation of forces in flow problems is devised and investigated. Finally, an approach for estimating the actual errors associated with the iterative solution of linear systems of equations is suggested. (author)
Fast converging minimum probability of error neural network receivers for DS-CDMA communications.
Matyjas, John D; Psaromiligkos, Ioannis N; Batalama, Stella N; Medley, Michael J
2004-03-01
We consider a multilayer perceptron neural network (NN) receiver architecture for the recovery of the information bits of a direct-sequence code-division-multiple-access (DS-CDMA) user. We develop a fast converging adaptive training algorithm that minimizes the bit-error rate (BER) at the output of the receiver. The adaptive algorithm has three key features: i) it incorporates the BER, i.e., the ultimate performance evaluation measure, directly into the learning process, ii) it utilizes constraints that are derived from the properties of the optimum single-user decision boundary for additive white Gaussian noise (AWGN) multiple-access channels, and iii) it embeds importance sampling (IS) principles directly into the receiver optimization process. Simulation studies illustrate the BER performance of the proposed scheme.
Radon measurements-discussion of error estimates for selected methods
International Nuclear Information System (INIS)
Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav
2010-01-01
The main sources of uncertainties for grab sampling, short-term (charcoal canisters) and long term (track detectors) measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. The origins of non-Poisson random errors during calibration are different for different kinds of instrumental measurements. The main sources of uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. It's shown that total measurement error of surface trap retrospective technique can be decreased to 35%.
On the mean squared error of the ridge estimator of the covariance and precision matrix
van Wieringen, Wessel N.
2017-01-01
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates the maximum likelihood regression estimator in terms of the mean squared error. Analogous results for the ridge maximum likelihood estimators of covariance and precision matrix are presented.
Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.
Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko
2017-06-01
Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.
Migliorati, Giovanni
2015-08-28
We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. The convergence estimates are given in mean-square sense with respect to the sampling measure. The noise may be correlated with the location of the evaluation and may have nonzero mean (offset). We consider both cases of bounded or square-integrable noise / offset. We prove conditions between the number of sampling points and the dimension of the underlying approximation space that ensure a stable and accurate approximation. Particular focus is on deriving estimates in probability within a given confidence level. We analyze how the best approximation error and the noise terms affect the convergence rate and the overall confidence level achieved by the convergence estimate. The proofs of our convergence estimates in probability use arguments from the theory of large deviations to bound the noise term. Finally we address the particular case of multivariate polynomial approximation spaces with any density in the beta family, including uniform and Chebyshev.
Energy Technology Data Exchange (ETDEWEB)
Reece, W.J.; Gilbert, B.G.; Richards, R.E. [EG and G Idaho, Inc., Idaho Falls, ID (United States)
1994-09-01
This data manual contains a hard copy of the information in the Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR) Version 3.5 database, which is sponsored by the US Nuclear Regulatory Commission. NUCLARR was designed as a tool for risk analysis. Many of the nuclear reactors in the US and several outside the US are represented in the NUCLARR database. NUCLARR includes both human error probability estimates for workers at the plants and hardware failure data for nuclear reactor equipment. Aggregations of these data yield valuable reliability estimates for probabilistic risk assessments and human reliability analyses. The data manual is organized to permit manual searches of the information if the computerized version is not available. Originally, the manual was published in three parts. In this revision the introductory material located in the original Part 1 has been incorporated into the text of Parts 2 and 3. The user can now find introductory material either in the original Part 1, or in Parts 2 and 3 as revised. Part 2 contains the human error probability data, and Part 3, the hardware component reliability data.
International Nuclear Information System (INIS)
Reece, W.J.; Gilbert, B.G.; Richards, R.E.
1994-09-01
This data manual contains a hard copy of the information in the Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR) Version 3.5 database, which is sponsored by the US Nuclear Regulatory Commission. NUCLARR was designed as a tool for risk analysis. Many of the nuclear reactors in the US and several outside the US are represented in the NUCLARR database. NUCLARR includes both human error probability estimates for workers at the plants and hardware failure data for nuclear reactor equipment. Aggregations of these data yield valuable reliability estimates for probabilistic risk assessments and human reliability analyses. The data manual is organized to permit manual searches of the information if the computerized version is not available. Originally, the manual was published in three parts. In this revision the introductory material located in the original Part 1 has been incorporated into the text of Parts 2 and 3. The user can now find introductory material either in the original Part 1, or in Parts 2 and 3 as revised. Part 2 contains the human error probability data, and Part 3, the hardware component reliability data
International Nuclear Information System (INIS)
Reece, W.J.; Gilbert, B.G.; Richards, R.E.
1994-09-01
This data manual contains a hard copy of the information in the Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR) Version 3.5 database, which is sponsored by the US Nuclear Regulatory Commission. NUCLARR was designed as a tool for risk analysis. Many of the nuclear reactors in the US and several outside the US are represented in the NUCLARR database. NUCLARR includes both human error probability estimates for workers at the plants and hardware failure data for nuclear reactor equipment. Aggregations of these data yield valuable reliability estimates for probabilistic risk assessments and human reliability analyses. The data manual is organized to permit manual searches of the information if the computerized version is not available. Originally, the manual was published in three parts. In this revision the introductory material located in the original Part 1 has been incorporated into the text of Parts 2 and 3. The user can now find introductory material either in the original Part 1, or in Parts 2 and 3 as revised. Part 2 contains the human error probability data, and Part 3, the hardware component reliability data
A procedure for estimation of pipe break probabilities due to IGSCC
International Nuclear Information System (INIS)
Bergman, M.; Brickstad, B.; Nilsson, F.
1998-06-01
A procedure has been developed for estimation of the failure probability of welds joints in nuclear piping susceptible to intergranular stress corrosion cracking. The procedure aims at a robust and rapid estimate of the failure probability for a specific weld with known stress state. Random properties are taken into account of the crack initiation rate, the initial crack length, the in-service inspection efficiency and the leak rate. A computer realization of the procedure has been developed for user friendly applications by design engineers. Some examples are considered to investigate the sensitivity of the failure probability to different input quantities. (au)
Silva, Ivair R
2018-01-15
Type I error probability spending functions are commonly used for designing sequential analysis of binomial data in clinical trials, but it is also quickly emerging for near-continuous sequential analysis of post-market drug and vaccine safety surveillance. It is well known that, for clinical trials, when the null hypothesis is not rejected, it is still important to minimize the sample size. Unlike in post-market drug and vaccine safety surveillance, that is not important. In post-market safety surveillance, specially when the surveillance involves identification of potential signals, the meaningful statistical performance measure to be minimized is the expected sample size when the null hypothesis is rejected. The present paper shows that, instead of the convex Type I error spending shape conventionally used in clinical trials, a concave shape is more indicated for post-market drug and vaccine safety surveillance. This is shown for both, continuous and group sequential analysis. Copyright © 2017 John Wiley & Sons, Ltd.
Unbiased multi-fidelity estimate of failure probability of a free plane jet
Marques, Alexandre; Kramer, Boris; Willcox, Karen; Peherstorfer, Benjamin
2017-11-01
Estimating failure probability related to fluid flows is a challenge because it requires a large number of evaluations of expensive models. We address this challenge by leveraging multiple low fidelity models of the flow dynamics to create an optimal unbiased estimator. In particular, we investigate the effects of uncertain inlet conditions in the width of a free plane jet. We classify a condition as failure when the corresponding jet width is below a small threshold, such that failure is a rare event (failure probability is smaller than 0.001). We estimate failure probability by combining the frameworks of multi-fidelity importance sampling and optimal fusion of estimators. Multi-fidelity importance sampling uses a low fidelity model to explore the parameter space and create a biasing distribution. An unbiased estimate is then computed with a relatively small number of evaluations of the high fidelity model. In the presence of multiple low fidelity models, this framework offers multiple competing estimators. Optimal fusion combines all competing estimators into a single estimator with minimal variance. We show that this combined framework can significantly reduce the cost of estimating failure probabilities, and thus can have a large impact in fluid flow applications. This work was funded by DARPA.
Yilmaz, Ferkan
2010-09-01
In this paper, we propose an analytical framework on the exact computation of the average symbol error probabilities (ASEP) of multihop transmission over generalized fading channels when an arbitrary number of amplify-and-forward relays is used. Our approach relies on moment generating function (MGF) framework to obtain exact single integral expressions which can be easily computed by Gauss-Chebyshev Quadrature (GCQ) rule. As such, the derived results are a convenient tool to analyze the ASEP performance of multihop transmission over amplify-and-forward relay fading channels. Numerical and simulation results, performed to verify the correctness of the proposed formulation, are in perfect agreement. © 2010 IEEE.
Yilmaz, Ferkan; Kucur, Oǧuz; Alouini, Mohamed-Slim
2010-01-01
In this paper, we propose an analytical framework on the exact computation of the average symbol error probabilities (ASEP) of multihop transmission over generalized fading channels when an arbitrary number of amplify-and-forward relays is used. Our approach relies on moment generating function (MGF) framework to obtain exact single integral expressions which can be easily computed by Gauss-Chebyshev Quadrature (GCQ) rule. As such, the derived results are a convenient tool to analyze the ASEP performance of multihop transmission over amplify-and-forward relay fading channels. Numerical and simulation results, performed to verify the correctness of the proposed formulation, are in perfect agreement. © 2010 IEEE.
Soury, Hamza
2012-06-01
This letter considers the average bit error probability of binary coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closed form expression in terms of the Fox\\'s H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading and Nakagami-m fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters. © 2012 IEEE.
Soury, Hamza
2013-07-01
This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.
Effects of exposure estimation errors on estimated exposure-response relations for PM2.5.
Cox, Louis Anthony Tony
2018-07-01
Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m 3 decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations. Copyright © 2018 Elsevier Inc. All rights reserved.
Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A
2017-11-01
Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
Energy Technology Data Exchange (ETDEWEB)
Nascimento, Claudio Souza do
2010-07-01
This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)
Energy Technology Data Exchange (ETDEWEB)
Ju, Lili; Tian, Li; Wang, Desheng
2008-10-31
In this paper, we present a residual-based a posteriori error estimate for the finite volume discretization of steady convection– diffusion–reaction equations defined on surfaces in R3, which are often implicitly represented as level sets of smooth functions. Reliability and efficiency of the proposed a posteriori error estimator are rigorously proved. Numerical experiments are also conducted to verify the theoretical results and demonstrate the robustness of the error estimator.
International Nuclear Information System (INIS)
Dundulis, Gintautas; Žutautaitė, Inga; Janulionis, Remigijus; Ušpuras, Eugenijus; Rimkevičius, Sigitas; Eid, Mohamed
2016-01-01
In this paper, the authors present an approach as an overall framework for the estimation of the failure probability of pipelines based on: the results of the deterministic-probabilistic structural integrity analysis (taking into account loads, material properties, geometry, boundary conditions, crack size, and defected zone thickness), the corrosion rate, the number of defects and failure data (involved into the model via application of Bayesian method). The proposed approach is applied to estimate the failure probability of a selected part of the Lithuanian natural gas transmission network. The presented approach for the estimation of integrated failure probability is a combination of several different analyses allowing us to obtain: the critical crack's length and depth, the failure probability of the defected zone thickness, dependency of the failure probability on the age of the natural gas transmission pipeline. A model's uncertainty analysis and uncertainty propagation analysis are performed, as well. - Highlights: • Degradation mechanisms of natural gas transmission pipelines. • Fracture mechanic analysis of the pipe with crack. • Stress evaluation of the pipe with critical crack. • Deterministic-probabilistic structural integrity analysis of gas pipeline. • Integrated estimation of pipeline failure probability by Bayesian method.
Pernot, Pascal; Savin, Andreas
2018-06-01
Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform end-users on the expected amplitude of prediction errors attached to these methods. We show that, the distributions of model errors being neither normal nor zero-centered, these error statistics cannot be used to infer prediction error probabilities. To overcome this limitation, we advocate for the use of more informative statistics, based on the empirical cumulative distribution function of unsigned errors, namely, (1) the probability for a new calculation to have an absolute error below a chosen threshold and (2) the maximal amplitude of errors one can expect with a chosen high confidence level. Those statistics are also shown to be well suited for benchmarking and ranking studies. Moreover, the standard error on all benchmarking statistics depends on the size of the reference dataset. Systematic publication of these standard errors would be very helpful to assess the statistical reliability of benchmarking conclusions.
Directory of Open Access Journals (Sweden)
Yun Shi
2014-01-01
Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.
Liang Yang,
2013-06-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we first consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation errors and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use them to evaluate the outage probability, error probability, and achievable rate. Subsequently, to investigate the joint effects of the channel estimation error and CCI on the system performance, we extend our analysis to a multiple-relay network and derive several asymptotic performance expressions. For comparison purposes, we also provide the analysis for the relay selection scheme under the total power constraint at the relays. For AF TWRN with channel estimation error and CCI, numerical results show that the performance of the relay selection scheme is not always better than that of the all-relay participating case. In particular, the relay selection scheme can improve the system performance in the case of high power levels at the sources and small powers at the relays.
Multifractals embedded in short time series: An unbiased estimation of probability moment
Qiu, Lu; Yang, Tianguang; Yin, Yanhua; Gu, Changgui; Yang, Huijie
2016-12-01
An exact estimation of probability moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called factorial-moment-based estimation of probability moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The factorial-moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed factorial moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.
Steam generator tubes rupture probability estimation - study of the axially cracked tube case
International Nuclear Information System (INIS)
Mavko, B.; Cizelj, L.; Roussel, G.
1992-01-01
The objective of the present study is to estimate the probability of a steam generator tube rupture due to the unstable propagation of axial through-wall cracks during a hypothetical accident. For this purpose the probabilistic fracture mechanics model was developed taking into account statistical distributions of influencing parameters. A numerical example considering a typical steam generator seriously affected by axial stress corrosion cracking in the roll transition area, is presented; it indicates the change of rupture probability with different assumptions focusing mostly on tubesheet reinforcing factor, crack propagation rate and crack detection probability. 8 refs., 4 figs., 4 tabs
Dopkins, Stephen; Varner, Kaitlin; Hoyer, Darin
2017-10-01
In word recognition semantic priming of test words increased the false-alarm rate and the mean of confidence ratings to lures. Such priming also increased the standard deviation of confidence ratings to lures and the slope of the z-ROC function, suggesting that the priming increased the standard deviation of the lure evidence distribution. The Unequal Variance Signal Detection (UVSD) model interpreted the priming as increasing the standard deviation of the lure evidence distribution. Without additional parameters the Dual Process Signal Detection (DPSD) model could only accommodate the results by fitting the data for related and unrelated primes separately, interpreting the priming, implausibly, as decreasing the probability of target recollection (DPSD). With an additional parameter, for the probability of false (lure) recollection the model could fit the data for related and unrelated primes together, interpreting the priming as increasing the probability of false recollection. These results suggest that DPSD estimates of target recollection probability will decrease with increases in the lure confidence/evidence standard deviation unless a parameter is included for false recollection. Unfortunately the size of a given lure confidence/evidence standard deviation relative to other possible lure confidence/evidence standard deviations is often unspecified by context. Hence the model often has no way of estimating false recollection probability and thereby correcting its estimates of target recollection probability.
First Passage Probability Estimation of Wind Turbines by Markov Chain Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.
2013-01-01
Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events...... of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal...... to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of the accuracy of the first passage probability estimation by the SS methods....
Measurement Error Affects Risk Estimates for Recruitment to the Hudson River Stock of Striped Bass
Directory of Open Access Journals (Sweden)
Dennis J. Dunning
2002-01-01
Full Text Available We examined the consequences of ignoring the distinction between measurement error and natural variability in an assessment of risk to the Hudson River stock of striped bass posed by entrainment at the Bowline Point, Indian Point, and Roseton power plants. Risk was defined as the probability that recruitment of age-1+ striped bass would decline by 80% or more, relative to the equilibrium value, at least once during the time periods examined (1, 5, 10, and 15 years. Measurement error, estimated using two abundance indices from independent beach seine surveys conducted on the Hudson River, accounted for 50% of the variability in one index and 56% of the variability in the other. If a measurement error of 50% was ignored and all of the variability in abundance was attributed to natural causes, the risk that recruitment of age-1+ striped bass would decline by 80% or more after 15 years was 0.308 at the current level of entrainment mortality (11%. However, the risk decreased almost tenfold (0.032 if a measurement error of 50% was considered. The change in risk attributable to decreasing the entrainment mortality rate from 11 to 0% was very small (0.009 and similar in magnitude to the change in risk associated with an action proposed in Amendment #5 to the Interstate Fishery Management Plan for Atlantic striped bass (0.006— an increase in the instantaneous fishing mortality rate from 0.33 to 0.4. The proposed increase in fishing mortality was not considered an adverse environmental impact, which suggests that potentially costly efforts to reduce entrainment mortality on the Hudson River stock of striped bass are not warranted.
Eppenhof, Koen A J; Pluim, Josien P W
2018-04-01
Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D convolutional neural network that learns to estimate registration errors from a pair of image patches. By applying the network to patches centered around every voxel, we construct registration error maps. The network is trained using a set of representative images that have been synthetically transformed to construct a set of image pairs with known deformations. The method is evaluated on deformable registrations of inhale-exhale pairs of thoracic CT scans. Using ground truth target registration errors on manually annotated landmarks, we evaluate the method's ability to estimate local registration errors. Estimation of full domain error maps is evaluated using a gold standard approach. The two evaluation approaches show that we can train the network to robustly estimate registration errors in a predetermined range, with subvoxel accuracy. We achieved a root-mean-square deviation of 0.51 mm from gold standard registration errors and of 0.66 mm from ground truth landmark registration errors.
The estimated lifetime probability of acquiring human papillomavirus in the United States.
Chesson, Harrell W; Dunne, Eileen F; Hariri, Susan; Markowitz, Lauri E
2014-11-01
Estimates of the lifetime probability of acquiring human papillomavirus (HPV) can help to quantify HPV incidence, illustrate how common HPV infection is, and highlight the importance of HPV vaccination. We developed a simple model, based primarily on the distribution of lifetime numbers of sex partners across the population and the per-partnership probability of acquiring HPV, to estimate the lifetime probability of acquiring HPV in the United States in the time frame before HPV vaccine availability. We estimated the average lifetime probability of acquiring HPV among those with at least 1 opposite sex partner to be 84.6% (range, 53.6%-95.0%) for women and 91.3% (range, 69.5%-97.7%) for men. Under base case assumptions, more than 80% of women and men acquire HPV by age 45 years. Our results are consistent with estimates in the existing literature suggesting a high lifetime probability of HPV acquisition and are supported by cohort studies showing high cumulative HPV incidence over a relatively short period, such as 3 to 5 years.
Száz, Dénes; Farkas, Alexandra; Barta, András; Kretzer, Balázs; Egri, Ádám; Horváth, Gábor
2016-07-01
The theory of sky-polarimetric Viking navigation has been widely accepted for decades without any information about the accuracy of this method. Previously, we have measured the accuracy of the first and second steps of this navigation method in psychophysical laboratory and planetarium experiments. Now, we have tested the accuracy of the third step in a planetarium experiment, assuming that the first and second steps are errorless. Using the fists of their outstretched arms, 10 test persons had to estimate the elevation angles (measured in numbers of fists and fingers) of black dots (representing the position of the occluded Sun) projected onto the planetarium dome. The test persons performed 2400 elevation estimations, 48% of which were more accurate than ±1°. We selected three test persons with the (i) largest and (ii) smallest elevation errors and (iii) highest standard deviation of the elevation error. From the errors of these three persons, we calculated their error function, from which the North errors (the angles with which they deviated from the geographical North) were determined for summer solstice and spring equinox, two specific dates of the Viking sailing period. The range of possible North errors Δ ω N was the lowest and highest at low and high solar elevations, respectively. At high elevations, the maximal Δ ω N was 35.6° and 73.7° at summer solstice and 23.8° and 43.9° at spring equinox for the best and worst test person (navigator), respectively. Thus, the best navigator was twice as good as the worst one. At solstice and equinox, high elevations occur the most frequently during the day, thus high North errors could occur more frequently than expected before. According to our findings, the ideal periods for sky-polarimetric Viking navigation are immediately after sunrise and before sunset, because the North errors are the lowest at low solar elevations.
A residual-based a posteriori error estimator for single-phase Darcy flow in fractured porous media
Chen, Huangxin; Sun, Shuyu
2016-01-01
for the problem with non-intersecting fractures. The reliability and efficiency of the a posteriori error estimator are established for the error measured in an energy norm. Numerical results verifying the robustness of the proposed a posteriori error estimator
Subroutine library for error estimation of matrix computation (Ver. 1.0)
International Nuclear Information System (INIS)
Ichihara, Kiyoshi; Shizawa, Yoshihisa; Kishida, Norio
1999-03-01
'Subroutine Library for Error Estimation of Matrix Computation' is a subroutine library which aids the users in obtaining the error ranges of the linear system's solutions or the Hermitian matrices' eigenvalues. This library contains routines for both sequential computers and parallel computers. The subroutines for linear system error estimation calculate norms of residual vectors, matrices's condition numbers, error bounds of solutions and so on. The subroutines for error estimation of Hermitian matrix eigenvalues derive the error ranges of the eigenvalues according to the Korn-Kato's formula. The test matrix generators supply the matrices appeared in the mathematical research, the ones randomly generated and the ones appeared in the application programs. This user's manual contains a brief mathematical background of error analysis on linear algebra and usage of the subroutines. (author)
Holmes, John B; Dodds, Ken G; Lee, Michael A
2017-03-02
An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.
DEFF Research Database (Denmark)
Tvedebrink, Torben; Eriksen, Poul Svante; Asplund, Maria
2012-01-01
We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out...... is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions....
International Nuclear Information System (INIS)
Jang, Inseok; Jung, Wondea; Seong, Poong Hyun
2016-01-01
Highlights: • The operation environment of MCRs in NPPs has changed by adopting digital HSIs. • Most current HRA databases are not explicitly designed to deal with digital HSI. • Empirical analysis for new HRA DB under an advanced MCR mockup are carried. • It is expected that the results can be used for advanced MCR HRA. - Abstract: Since the Three Mile Island (TMI)-2 accident, human error has been recognized as one of the main causes of Nuclear Power Plant (NPP) accidents, and numerous studies related to Human Reliability Analysis (HRA) have been carried out. Most of these studies were focused on considering the conventional Main Control Room (MCR) environment. However, the operating environment of MCRs in NPPs has changed with the adoption of new human-system interfaces (HSI) largely based on up-to-date digital technologies. The MCRs that include these digital and computer technologies, such as large display panels, computerized procedures, and soft controls, are called advanced MCRs. Among the many features of advanced MCRs, soft controls are a particularly important because operating actions in advanced MCRs are performed by soft control. Due to the difference in interfaces between soft control and hardwired conventional controls, different HEP should be used in the HRA for advanced MCRs. Unfortunately, most current HRA databases deal with operations in conventional MCRs and are not explicitly designed to deal with digital Human System Interface (HSI). For this reason, empirical human error and the associated error recovery probabilities were collected from the mockup of an advanced MCR equipped with soft controls. To this end, small-scaled experiments are conducted with 48 graduated students in the department of nuclear engineering in Korea Advanced Institute of Science and Technology (KAIST) are participated, and accident scenarios are designed with respect to the typical Design Basis Accidents (DBAs) in NPPs, such as Steam Generator Tube Rupture
Estimating and localizing the algebraic and total numerical errors using flux reconstructions
Czech Academy of Sciences Publication Activity Database
Papež, Jan; Strakoš, Z.; Vohralík, M.
2018-01-01
Roč. 138, č. 3 (2018), s. 681-721 ISSN 0029-599X R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : numerical solution of partial differential equations * finite element method * a posteriori error estimation * algebraic error * discretization error * stopping criteria * spatial distribution of the error Subject RIV: BA - General Mathematics Impact factor: 2.152, year: 2016
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
Du, Shaohong; Sun, Shuyu; Xie, Xiaoping
2015-01-01
A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
Du, Shaohong
2015-10-26
A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.
Mandal, S.; Choudhury, B. U.
2015-07-01
Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.
Kim, ChangHwan; Tamborini, Christopher R.
2012-01-01
Few studies have considered how earnings inequality estimates may be affected by measurement error in self-reported earnings in surveys. Utilizing restricted-use data that links workers in the Survey of Income and Program Participation with their W-2 earnings records, we examine the effect of measurement error on estimates of racial earnings…
Ambros Berger; Thomas Gschwantner; Ronald E. McRoberts; Klemens. Schadauer
2014-01-01
National forest inventories typically estimate individual tree volumes using models that rely on measurements of predictor variables such as tree height and diameter, both of which are subject to measurement error. The aim of this study was to quantify the impacts of these measurement errors on the uncertainty of the model-based tree stem volume estimates. The impacts...
Error estimates for ice discharge calculated using the flux gate approach
Navarro, F. J.; Sánchez Gámez, P.
2017-12-01
Ice discharge to the ocean is usually estimated using the flux gate approach, in which ice flux is calculated through predefined flux gates close to the marine glacier front. However, published results usually lack a proper error estimate. In the flux calculation, both errors in cross-sectional area and errors in velocity are relevant. While for estimating the errors in velocity there are well-established procedures, the calculation of the error in the cross-sectional area requires the availability of ground penetrating radar (GPR) profiles transverse to the ice-flow direction. In this contribution, we use IceBridge operation GPR profiles collected in Ellesmere and Devon Islands, Nunavut, Canada, to compare the cross-sectional areas estimated using various approaches with the cross-sections estimated from GPR ice-thickness data. These error estimates are combined with those for ice-velocities calculated from Sentinel-1 SAR data, to get the error in ice discharge. Our preliminary results suggest, regarding area, that the parabolic cross-section approaches perform better than the quartic ones, which tend to overestimate the cross-sectional area for flight lines close to the central flowline. Furthermore, the results show that regional ice-discharge estimates made using parabolic approaches provide reasonable results, but estimates for individual glaciers can have large errors, up to 20% in cross-sectional area.
Eppenhof, K.A.J.; Pluim, J.P.W.
2018-01-01
Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D
Eppenhof, Koen A.J.; Pluim, Josien P.W.; Styner, M.A.; Angelini, E.D.
2017-01-01
Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation
Performances of estimators of linear auto-correlated error model ...
African Journals Online (AJOL)
The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...
Yilmaz, Ferkan
2012-07-01
Analysis of the average binary error probabilities (ABEP) and average capacity (AC) of wireless communications systems over generalized fading channels have been considered separately in past years. This paper introduces a novel moment generating function (MGF)-based unified expression for the ABEP and AC of single and multiple link communications with maximal ratio combining. In addition, this paper proposes the hyper-Fox\\'s H fading model as a unified fading distribution of a majority of the well-known generalized fading environments. As such, the authors offer a generic unified performance expression that can be easily calculated, and that is applicable to a wide variety of fading scenarios. The mathematical formulism is illustrated with some selected numerical examples that validate the correctness of the authors\\' newly derived results. © 1972-2012 IEEE.
Yilmaz, Ferkan
2014-04-01
The main idea in the moment generating function (MGF) approach is to alternatively express the conditional bit error probability (BEP) in a desired exponential form so that possibly multi-fold performance averaging is readily converted into a computationally efficient single-fold averaging - sometimes into a closed-form - by means of using the MGF of the signal-to-noise ratio. However, as presented in [1] and specifically indicated in [2] and also to the best of our knowledge, there does not exist an MGF-based approach in the literature to represent Wojnar\\'s generic BEP expression in a desired exponential form. This paper presents novel MGF-based expressions for calculating the average BEP of binary signalling over generalized fading channels, specifically by expressing Wojnar\\'s generic BEP expression in a desirable exponential form. We also propose MGF-based expressions to explore the amount of dispersion in the BEP for binary signalling over generalized fading channels.
Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.
Directory of Open Access Journals (Sweden)
Michael F Sloma
2017-11-01
Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.
Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.
Sloma, Michael F; Mathews, David H
2017-11-01
Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.
Estimation of component failure probability from masked binomial system testing data
International Nuclear Information System (INIS)
Tan Zhibin
2005-01-01
The component failure probability estimates from analysis of binomial system testing data are very useful because they reflect the operational failure probability of components in the field which is similar to the test environment. In practice, this type of analysis is often confounded by the problem of data masking: the status of tested components is unknown. Methods in considering this type of uncertainty are usually computationally intensive and not practical to solve the problem for complex systems. In this paper, we consider masked binomial system testing data and develop a probabilistic model to efficiently estimate component failure probabilities. In the model, all system tests are classified into test categories based on component coverage. Component coverage of test categories is modeled by a bipartite graph. Test category failure probabilities conditional on the status of covered components are defined. An EM algorithm to estimate component failure probabilities is developed based on a simple but powerful concept: equivalent failures and tests. By simulation we not only demonstrate the convergence and accuracy of the algorithm but also show that the probabilistic model is capable of analyzing systems in series, parallel and any other user defined structures. A case study illustrates an application in test case prioritization
A note on estimating errors from the likelihood function
International Nuclear Information System (INIS)
Barlow, Roger
2005-01-01
The points at which the log likelihood falls by 12 from its maximum value are often used to give the 'errors' on a result, i.e. the 68% central confidence interval. The validity of this is examined for two simple cases: a lifetime measurement and a Poisson measurement. Results are compared with the exact Neyman construction and with the simple Bartlett approximation. It is shown that the accuracy of the log likelihood method is poor, and the Bartlett construction explains why it is flawed
LiDAR error estimation with WAsP engineering
DEFF Research Database (Denmark)
Bingöl, Ferhat; Mann, Jakob; Foussekis, D.
2008-01-01
The LiDAR measurements, vertical wind profile in any height between 10 to 150m, are based on assumption that the measured wind is a product of a homogenous wind. In reality there are many factors affecting the wind on each measurement point which the terrain plays the main role. To model Li......DAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met. mast data have been collected and the same conditions are simulated with Riso/DTU software, WAsP Engineering 2.0. Finally measurement...
Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters.
Song, Jin Woo; Park, Chan Gook
2018-04-21
An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.
International Nuclear Information System (INIS)
Gilmore, W.E.; Gertman, D.I.; Gilbert, B.G.; Reece, W.J.
1988-11-01
The Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR) is an automated data base management system for processing and storing human error probability (HEP) and hardware component failure data (HCFD). The NUCLARR system software resides on an IBM (or compatible) personal micro-computer. Users can perform data base searches to furnish HEP estimates and HCFD rates. In this manner, the NUCLARR system can be used to support a variety of risk assessment activities. This volume, Volume 3 of a 5-volume series, presents the procedures used to process HEP and HCFD for entry in NUCLARR and describes how to modify the existing NUCLARR taxonomy in order to add either equipment types or action verbs. Volume 3 also specifies the various roles of the administrative staff on assignment to the NUCLARR Clearinghouse who are tasked with maintaining the data base, dealing with user requests, and processing NUCLARR data. 5 refs., 34 figs., 3 tabs
A method for estimating failure rates for low probability events arising in PSA
International Nuclear Information System (INIS)
Thorne, M.C.; Williams, M.M.R.
1995-01-01
The authors develop a method for predicting failure rates and failure probabilities per event when, over a given test period or number of demands, no failures have occurred. A Bayesian approach is adopted to calculate a posterior probability distribution for the failure rate or failure probability per event subsequent to the test period. This posterior is then used to estimate effective failure rates or probabilities over a subsequent period of time or number of demands. In special circumstances, the authors results reduce to the well-known rules of thumb, viz: 1/N and 1/T, where N is the number of demands during the test period for no failures and T is the test period for no failures. However, the authors are able to give strict conditions on the validity of these rules of thumb and to improve on them when necessary
International Nuclear Information System (INIS)
Johnson, D.P.; Toomay, T.L.; Davis, C.S.
1979-02-01
An inspection uncertainty analysis of published PVRC Specimen 201 data is reported to obtain an estimate of the probability of recording an indication as a function of imperfection height for ASME Section XI Code ultrasonic inspections of the nuclear reactor vessel plate seams and to demonstrate the advantages of inspection uncertainty analysis over conventional detection/nondetection counting analysis. This analysis found the probability of recording a significant defect with an ASME Section XI Code ultrasonic inspection to be very high, if such a defect should exist in the plate seams of a nuclear reactor vessel. For a one-inch high crack, for example, this analysis gives a best estimate recording probability of .985 and a 90% lower confidence bound recording probabilty of .937. It is also shown that inspection uncertainty analysis gives more accurate estimates and gives estimates over a much greater flaw size range than is possible with conventional analysis. There is reason to believe that the estimation procedure used is conservative, the estimation is based on data generated several years ago, on very small defects, in an environment that is different from the actual in-service inspection environment
International Nuclear Information System (INIS)
Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing
2012-01-01
In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)
Mediators of the Availability Heuristic in Probability Estimates of Future Events.
Levi, Ariel S.; Pryor, John B.
Individuals often estimate the probability of future events by the ease with which they can recall or cognitively construct relevant instances. Previous research has not precisely identified the cognitive processes mediating this "availability heuristic." Two potential mediators (imagery of the event, perceived reasons or causes for the…
Estimating the Probability of a Rare Event Over a Finite Time Horizon
de Boer, Pieter-Tjerk; L'Ecuyer, Pierre; Rubino, Gerardo; Tuffin, Bruno
2007-01-01
We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the chain reaches a given set of states before some fixed time limit. The jump rates of the chain are expressed as functions of
Estimating success probability of a rugby goal kick and developing a ...
African Journals Online (AJOL)
The objective of this study was firstly to derive a formula to estimate the success probability of a particular rugby goal kick and, secondly to derive a goal kicker rating measure that could be used to rank rugby union goal kickers. Various factors that could influence the success of a particular goal kick were considered.
Institute of Scientific and Technical Information of China (English)
Xiaogu ZHENG
2009-01-01
An adaptive estimation of forecast error covariance matrices is proposed for Kalman filtering data assimilation. A forecast error covariance matrix is initially estimated using an ensemble of perturbation forecasts. This initially estimated matrix is then adjusted with scale parameters that are adaptively estimated by minimizing -2log-likelihood of observed-minus-forecast residuals. The proposed approach could be applied to Kalman filtering data assimilation with imperfect models when the model error statistics are not known. A simple nonlinear model (Burgers' equation model) is used to demonstrate the efficacy of the proposed approach.
International Nuclear Information System (INIS)
Zio, E.; Pedroni, N.
2010-01-01
The quantitative reliability assessment of a thermal-hydraulic (T-H) passive safety system of a nuclear power plant can be obtained by (i) Monte Carlo (MC) sampling the uncertainties of the system model and parameters, (ii) computing, for each sample, the system response by a mechanistic T-H code and (iii) comparing the system response with pre-established safety thresholds, which define the success or failure of the safety function. The computational effort involved can be prohibitive because of the large number of (typically long) T-H code simulations that must be performed (one for each sample) for the statistical estimation of the probability of success or failure. In this work, Line Sampling (LS) is adopted for efficient MC sampling. In the LS method, an 'important direction' pointing towards the failure domain of interest is determined and a number of conditional one-dimensional problems are solved along such direction; this allows for a significant reduction of the variance of the failure probability estimator, with respect, for example, to standard random sampling. Two issues are still open with respect to LS: first, the method relies on the determination of the 'important direction', which requires additional runs of the T-H code; second, although the method has been shown to improve the computational efficiency by reducing the variance of the failure probability estimator, no evidence has been given yet that accurate and precise failure probability estimates can be obtained with a number of samples reduced to below a few hundreds, which may be required in case of long-running models. The work presented in this paper addresses the first issue by (i) quantitatively comparing the efficiency of the methods proposed in the literature to determine the LS important direction; (ii) employing artificial neural network (ANN) regression models as fast-running surrogates of the original, long-running T-H code to reduce the computational cost associated to the
Errors and parameter estimation in precipitation-runoff modeling: 1. Theory
Troutman, Brent M.
1985-01-01
Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.
International Nuclear Information System (INIS)
Hwang, Meejeong; Kang, Dae Il
2011-01-01
Highlights: ► This paper presents a method to estimate the common cause failure probabilities on the common cause component group with mixed testing schemes. ► The CCF probabilities are dependent on the testing schemes such as staggered testing or non-staggered testing. ► There are many CCCGs with specific mixed testing schemes in real plant operation. ► Therefore, a general formula which is applicable to both alternate periodic testing scheme and train level mixed testing scheme was derived. - Abstract: This paper presents a method to estimate the common cause failure (CCF) probabilities on the common cause component group (CCCG) with mixed testing schemes such as the train level mixed testing scheme or the alternate periodic testing scheme. In the train level mixed testing scheme, the components are tested in a non-staggered way within the same train, but the components are tested in a staggered way between the trains. The alternate periodic testing scheme indicates that all components in the same CCCG are tested in a non-staggered way during the planned maintenance period, but they are tested in a staggered way during normal plant operation. Since the CCF probabilities are dependent on the testing schemes such as staggered testing or non-staggered testing, CCF estimators have two kinds of formulas in accordance with the testing schemes. Thus, there are general formulas to estimate the CCF probability on the staggered testing scheme and non-staggered testing scheme. However, in real plant operation, there are many CCCGs with specific mixed testing schemes. Recently, Barros () and Kang () proposed a CCF factor estimation method to reflect the alternate periodic testing scheme and the train level mixed testing scheme. In this paper, a general formula which is applicable to both the alternate periodic testing scheme and the train level mixed testing scheme was derived.
Investigation of error sources in regional inverse estimates of greenhouse gas emissions in Canada
Chan, E.; Chan, D.; Ishizawa, M.; Vogel, F.; Brioude, J.; Delcloo, A.; Wu, Y.; Jin, B.
2015-08-01
Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion
A posteriori error estimator and AMR for discrete ordinates nodal transport methods
International Nuclear Information System (INIS)
Duo, Jose I.; Azmy, Yousry Y.; Zikatanov, Ludmil T.
2009-01-01
In the development of high fidelity transport solvers, optimization of the use of available computational resources and access to a tool for assessing quality of the solution are key to the success of large-scale nuclear systems' simulation. In this regard, error control provides the analyst with a confidence level in the numerical solution and enables for optimization of resources through Adaptive Mesh Refinement (AMR). In this paper, we derive an a posteriori error estimator based on the nodal solution of the Arbitrarily High Order Transport Method of the Nodal type (AHOT-N). Furthermore, by making assumptions on the regularity of the solution, we represent the error estimator as a function of computable volume and element-edges residuals. The global L 2 error norm is proved to be bound by the estimator. To lighten the computational load, we present a numerical approximation to the aforementioned residuals and split the global norm error estimator into local error indicators. These indicators are used to drive an AMR strategy for the spatial discretization. However, the indicators based on forward solution residuals alone do not bound the cell-wise error. The estimator and AMR strategy are tested in two problems featuring strong heterogeneity and highly transport streaming regime with strong flux gradients. The results show that the error estimator indeed bounds the global error norms and that the error indicator follows the cell-error's spatial distribution pattern closely. The AMR strategy proves beneficial to optimize resources, primarily by reducing the number of unknowns solved for to achieve prescribed solution accuracy in global L 2 error norm. Likewise, AMR achieves higher accuracy compared to uniform refinement when resolving sharp flux gradients, for the same number of unknowns
Langtimm, C.A.; O'Shea, T.J.; Pradel, R.; Beck, C.A.
1998-01-01
The population dynamics of large, long-lived mammals are particularly sensitive to changes in adult survival. Understanding factors affecting survival patterns is therefore critical for developing and testing theories of population dynamics and for developing management strategies aimed at preventing declines or extinction in such taxa. Few studies have used modern analytical approaches for analyzing variation and testing hypotheses about survival probabilities in large mammals. This paper reports a detailed analysis of annual adult survival in the Florida manatee (Trichechus manatus latirostris), an endangered marine mammal, based on a mark-recapture approach. Natural and boat-inflicted scars distinctively 'marked' individual manatees that were cataloged in a computer-based photographic system. Photo-documented resightings provided 'recaptures.' Using open population models, annual adult-survival probabilities were estimated for manatees observed in winter in three areas of Florida: Blue Spring, Crystal River, and the Atlantic coast. After using goodness-of-fit tests in Program RELEASE to search for violations of the assumptions of mark-recapture analysis, survival and sighting probabilities were modeled under several different biological hypotheses with Program SURGE. Estimates of mean annual probability of sighting varied from 0.948 for Blue Spring to 0.737 for Crystal River and 0.507 for the Atlantic coast. At Crystal River and Blue Spring, annual survival probabilities were best estimated as constant over the study period at 0.96 (95% CI = 0.951-0.975 and 0.900-0.985, respectively). On the Atlantic coast, where manatees are impacted more by human activities, annual survival probabilities had a significantly lower mean estimate of 0.91 (95% CI = 0.887-0.926) and varied unpredictably over the study period. For each study area, survival did not differ between sexes and was independent of relative adult age. The high constant adult-survival probabilities estimated
Improved estimates of coordinate error for molecular replacement
International Nuclear Information System (INIS)
Oeffner, Robert D.; Bunkóczi, Gábor; McCoy, Airlie J.; Read, Randy J.
2013-01-01
A function for estimating the effective root-mean-square deviation in coordinates between two proteins has been developed that depends on both the sequence identity and the size of the protein and is optimized for use with molecular replacement in Phaser. A top peak translation-function Z-score of over 8 is found to be a reliable metric of when molecular replacement has succeeded. The estimate of the root-mean-square deviation (r.m.s.d.) in coordinates between the model and the target is an essential parameter for calibrating likelihood functions for molecular replacement (MR). Good estimates of the r.m.s.d. lead to good estimates of the variance term in the likelihood functions, which increases signal to noise and hence success rates in the MR search. Phaser has hitherto used an estimate of the r.m.s.d. that only depends on the sequence identity between the model and target and which was not optimized for the MR likelihood functions. Variance-refinement functionality was added to Phaser to enable determination of the effective r.m.s.d. that optimized the log-likelihood gain (LLG) for a correct MR solution. Variance refinement was subsequently performed on a database of over 21 000 MR problems that sampled a range of sequence identities, protein sizes and protein fold classes. Success was monitored using the translation-function Z-score (TFZ), where a TFZ of 8 or over for the top peak was found to be a reliable indicator that MR had succeeded for these cases with one molecule in the asymmetric unit. Good estimates of the r.m.s.d. are correlated with the sequence identity and the protein size. A new estimate of the r.m.s.d. that uses these two parameters in a function optimized to fit the mean of the refined variance is implemented in Phaser and improves MR outcomes. Perturbing the initial estimate of the r.m.s.d. from the mean of the distribution in steps of standard deviations of the distribution further increases MR success rates
PERFORMANCE OF THE ZERO FORCING PRECODING MIMO BROADCAST SYSTEMS WITH CHANNEL ESTIMATION ERRORS
Institute of Scientific and Technical Information of China (English)
Wang Jing; Liu Zhanli; Wang Yan; You Xiaohu
2007-01-01
In this paper, the effect of channel estimation errors upon the Zero Forcing (ZF) precoding Multiple Input Multiple Output Broadcast (MIMO BC) systems was studied. Based on the two kinds of Gaussian estimation error models, the performance analysis is conducted under different power allocation strategies. Analysis and simulation show that if the covariance of channel estimation errors is independent of the received Signal to Noise Ratio (SNR), imperfect channel knowledge deteriorates the sum capacity and the Bit Error Rate (BER) performance severely. However, under the situation of orthogonal training and the Minimum Mean Square Error (MMSE) channel estimation, the sum capacity and BER performance are consistent with those of the perfect Channel State Information (CSI)with only a performance degradation.
Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors
DEFF Research Database (Denmark)
Nguyen, Chuyen T.; Hayashi, Kazunori; Kaneko, Megumi
2013-01-01
Abstract Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio...... is evaluated under dierent system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol. Keywords RFID tag cardinality estimation maximum likelihood detection error...
Measurement Error in Income and Schooling and the Bias of Linear Estimators
DEFF Research Database (Denmark)
Bingley, Paul; Martinello, Alessandro
2017-01-01
and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators......We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing...
Sandberg, Mattias
2015-01-07
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with log normal distributed diffusion coefficients, e.g. modelling ground water flow. Typical models use log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. This talk will address how the total error can be estimated by the computable error.
On the Estimation of Standard Errors in Cognitive Diagnosis Models
Philipp, Michel; Strobl, Carolin; de la Torre, Jimmy; Zeileis, Achim
2018-01-01
Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare different versions of CDMs, or to check model…
Gap filling strategies and error in estimating annual soil respiration
Soil respiration (Rsoil) is one of the largest CO2 fluxes in the global carbon (C) cycle. Estimation of annual Rsoil requires extrapolation of survey measurements or gap-filling of automated records to produce a complete time series. While many gap-filling methodologies have been employed, there is ...
Hall, Eric
2016-01-09
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with lognormal distributed diffusion coefficients, e.g. modeling ground water flow. Typical models use lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. We address how the total error can be estimated by the computable error.
Energy Technology Data Exchange (ETDEWEB)
Kim, Myungsu; Lim, Heoksoon; Na, Janghwan; Chi, Moongoo [Korea Hydro and Nuclear Power Co. Ltd. Central Research Institute, Daejeon (Korea, Republic of)
2015-05-15
It is focusing on development of a new designing process which can be compatible to international standards such as IAEA1 and NRC2 suggest. Evaluation for the design effectiveness was found as one of the areas to improve. If a design doesn't meet a certain level of effectiveness, it should be re-designed accordingly. The effectiveness can be calculated with combination of probability of Interruption and probability of neutralization. System Analysis of Vulnerability to Intrusion (SAVI) has been developed by Sandia National Laboratories for that purpose. With SNL's timely detection methodology, SAVI has been used by U.S. nuclear utilities to meet the NRC requirements for PPS design effectiveness evaluation. For the SAVI calculation, probability of neutralization is a vital input element that must be supplied. This paper describes the elements to consider for neutralization, probability estimation methodology, and the estimation for APR1400 PPS design effectiveness evaluation process. Markov chain and Monte Carlo simulation are often used for simple numerical calculation to estimate P{sub N}. The results from both methods are not always identical even for the same situation. P{sub N} values for APR1400 evaluation were calculated based on Markov chain method and modified to be applicable for guards/adversaries ratio based analysis.
Michael, Andrew J.
2012-01-01
Estimates of the probability that an ML 4.8 earthquake, which occurred near the southern end of the San Andreas fault on 24 March 2009, would be followed by an M 7 mainshock over the following three days vary from 0.0009 using a Gutenberg–Richter model of aftershock statistics (Reasenberg and Jones, 1989) to 0.04 using a statistical model of foreshock behavior and long‐term estimates of large earthquake probabilities, including characteristic earthquakes (Agnew and Jones, 1991). I demonstrate that the disparity between the existing approaches depends on whether or not they conform to Gutenberg–Richter behavior. While Gutenberg–Richter behavior is well established over large regions, it could be violated on individual faults if they have characteristic earthquakes or over small areas if the spatial distribution of large‐event nucleations is disproportional to the rate of smaller events. I develop a new form of the aftershock model that includes characteristic behavior and combines the features of both models. This new model and the older foreshock model yield the same results when given the same inputs, but the new model has the advantage of producing probabilities for events of all magnitudes, rather than just for events larger than the initial one. Compared with the aftershock model, the new model has the advantage of taking into account long‐term earthquake probability models. Using consistent parameters, the probability of an M 7 mainshock on the southernmost San Andreas fault is 0.0001 for three days from long‐term models and the clustering probabilities following the ML 4.8 event are 0.00035 for a Gutenberg–Richter distribution and 0.013 for a characteristic‐earthquake magnitude–frequency distribution. Our decisions about the existence of characteristic earthquakes and how large earthquakes nucleate have a first‐order effect on the probabilities obtained from short‐term clustering models for these large events.
Directory of Open Access Journals (Sweden)
Jiang Ge
2017-01-01
Full Text Available System degradation was usually caused by multiple-parameter degradation. The assessment result of system reliability by universal generating function was low accurate when compared with the Monte Carlo simulation. And the probability density function of the system output performance cannot be got. So the reliability assessment method based on the probability density evolution with multi-parameter was presented for complexly degraded system. Firstly, the system output function was founded according to the transitive relation between component parameters and the system output performance. Then, the probability density evolution equation based on the probability conservation principle and the system output function was established. Furthermore, probability distribution characteristics of the system output performance was obtained by solving differential equation. Finally, the reliability of the degraded system was estimated. This method did not need to discrete the performance parameters and can establish continuous probability density function of the system output performance with high calculation efficiency and low cost. Numerical example shows that this method is applicable to evaluate the reliability of multi-parameter degraded system.
A method for the estimation of the probability of damage due to earthquakes
International Nuclear Information System (INIS)
Alderson, M.A.H.G.
1979-07-01
The available information on seismicity within the United Kingdom has been combined with building damage data from the United States to produce a method of estimating the probability of damage to structures due to the occurrence of earthquakes. The analysis has been based on the use of site intensity as the major damage producing parameter. Data for structural, pipework and equipment items have been assumed and the overall probability of damage calculated as a function of the design level. Due account is taken of the uncertainties of the seismic data. (author)
Directory of Open Access Journals (Sweden)
Martinásková Magdalena
2017-12-01
Full Text Available The article examines the use of Asymptotic Sampling (AS for the estimation of failure probability. The AS algorithm requires samples of multidimensional Gaussian random vectors, which may be obtained by many alternative means that influence the performance of the AS method. Several reliability problems (test functions have been selected in order to test AS with various sampling schemes: (i Monte Carlo designs; (ii LHS designs optimized using the Periodic Audze-Eglājs (PAE criterion; (iii designs prepared using Sobol’ sequences. All results are compared with the exact failure probability value.
A fast algorithm for estimating transmission probabilities in QTL detection designs with dense maps
Directory of Open Access Journals (Sweden)
Gilbert Hélène
2009-11-01
Full Text Available Abstract Background In the case of an autosomal locus, four transmission events from the parents to progeny are possible, specified by the grand parental origin of the alleles inherited by this individual. Computing the probabilities of these transmission events is essential to perform QTL detection methods. Results A fast algorithm for the estimation of these probabilities conditional to parental phases has been developed. It is adapted to classical QTL detection designs applied to outbred populations, in particular to designs composed of half and/or full sib families. It assumes the absence of interference. Conclusion The theory is fully developed and an example is given.
Nonparametric Estimation of Regression Parameters in Measurement Error Models
Czech Academy of Sciences Publication Activity Database
Ehsanes Saleh, A.K.M.D.; Picek, J.; Kalina, Jan
2009-01-01
Roč. 67, č. 2 (2009), s. 177-200 ISSN 0026-1424 Grant - others:GA AV ČR(CZ) IAA101120801; GA MŠk(CZ) LC06024 Institutional research plan: CEZ:AV0Z10300504 Keywords : asymptotic relative efficiency(ARE) * asymptotic theory * emaculate mode * Me model * R-estimation * Reliabilty ratio(RR) Subject RIV: BB - Applied Statistics, Operational Research
Zollanvari, Amin
2013-05-24
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Zollanvari, Amin; Genton, Marc G.
2013-01-01
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model
Rizvi, Farheen
2016-01-01
Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.
An Extended Quadratic Frobenius Primality Test with Average and Worst Case Error Estimates
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2003-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
An Extended Quadratic Frobenius Primality Test with Average- and Worst-Case Error Estimate
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2006-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
An Extended Quadratic Frobenius Primality Test with Average Case Error Estimates
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2001-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
Component Analysis of Errors on PERSIANN Precipitation Estimates over Urmia Lake Basin, IRAN
Ghajarnia, N.; Daneshkar Arasteh, P.; Liaghat, A. M.; Araghinejad, S.
2016-12-01
In this study, PERSIANN daily dataset is evaluated from 2000 to 2011 in 69 pixels over Urmia Lake basin in northwest of Iran. Different analytical approaches and indexes are used to examine PERSIANN precision in detection and estimation of rainfall rate. The residuals are decomposed into Hit, Miss and FA estimation biases while continues decomposition of systematic and random error components are also analyzed seasonally and categorically. New interpretation of estimation accuracy named "reliability on PERSIANN estimations" is introduced while the changing manners of existing categorical/statistical measures and error components are also seasonally analyzed over different rainfall rate categories. This study yields new insights into the nature of PERSIANN errors over Urmia lake basin as a semi-arid region in the middle-east, including the followings: - The analyzed contingency table indexes indicate better detection precision during spring and fall. - A relatively constant level of error is generally observed among different categories. The range of precipitation estimates at different rainfall rate categories is nearly invariant as a sign for the existence of systematic error. - Low level of reliability is observed on PERSIANN estimations at different categories which are mostly associated with high level of FA error. However, it is observed that as the rate of precipitation increase, the ability and precision of PERSIANN in rainfall detection also increases. - The systematic and random error decomposition in this area shows that PERSIANN has more difficulty in modeling the system and pattern of rainfall rather than to have bias due to rainfall uncertainties. The level of systematic error also considerably increases in heavier rainfalls. It is also important to note that PERSIANN error characteristics at each season varies due to the condition and rainfall patterns of that season which shows the necessity of seasonally different approach for the calibration of
DEFF Research Database (Denmark)
Voigt, Andreas Jauernik; Santos, Ilmar
2012-01-01
to ∼ 20% of the nominal air gap the force estimation error is found to be reduced by the linearized force equation as compared to the quadratic force equation, which is supported by experimental results. Additionally the FE model is employed in a comparative study of the force estimation error behavior...... of AMBs by embedding Hall sensors instead of mounting these directly on the pole surfaces, force estimation errors are investigated both numerically and experimentally. A linearized version of the conventionally applied quadratic correspondence between measured Hall voltage and applied AMB force...
Estimation of submarine mass failure probability from a sequence of deposits with age dates
Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.
2013-01-01
The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.
The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation
Felder, Guido; Zischg, Andreas; Weingartner, Rolf
2017-07-01
Deterministic rainfall-runoff modelling usually assumes stationary hydrological system, as model parameters are calibrated with and therefore dependant on observed data. However, runoff processes are probably not stationary in the case of a probable maximum flood (PMF) where discharge greatly exceeds observed flood peaks. Developing hydrodynamic models and using them to build coupled hydrologic-hydrodynamic models can potentially improve the plausibility of PMF estimations. This study aims to assess the potential benefits and constraints of coupled modelling compared to standard deterministic hydrologic modelling when it comes to PMF estimation. The two modelling approaches are applied using a set of 100 spatio-temporal probable maximum precipitation (PMP) distribution scenarios. The resulting hydrographs, the resulting peak discharges as well as the reliability and the plausibility of the estimates are evaluated. The discussion of the results shows that coupling hydrologic and hydrodynamic models substantially improves the physical plausibility of PMF modelling, although both modelling approaches lead to PMF estimations for the catchment outlet that fall within a similar range. Using a coupled model is particularly suggested in cases where considerable flood-prone areas are situated within a catchment.
A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem
Delaigle, Aurore
2009-03-01
Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.
On systematic and statistic errors in radionuclide mass activity estimation procedure
International Nuclear Information System (INIS)
Smelcerovic, M.; Djuric, G.; Popovic, D.
1989-01-01
One of the most important requirements during nuclear accidents is the fast estimation of the mass activity of the radionuclides that suddenly and without control reach the environment. The paper points to systematic errors in the procedures of sampling, sample preparation and measurement itself, that in high degree contribute to total mass activity evaluation error. Statistic errors in gamma spectrometry as well as in total mass alpha and beta activity evaluation are also discussed. Beside, some of the possible sources of errors in the partial mass activity evaluation for some of the radionuclides are presented. The contribution of the errors in the total mass activity evaluation error is estimated and procedures that could possibly reduce it are discussed (author)
Annotated corpus and the empirical evaluation of probability estimates of grammatical forms
Directory of Open Access Journals (Sweden)
Ševa Nada
2003-01-01
Full Text Available The aim of the present study is to demonstrate the usage of an annotated corpus in the field of experimental psycholinguistics. Specifically, we demonstrate how the manually annotated Corpus of Serbian Language (Kostić, Đ. 2001 can be used for probability estimates of grammatical forms, which allow the control of independent variables in psycholinguistic experiments. We address the issue of processing Serbian inflected forms within two subparadigms of feminine nouns. In regression analysis, almost all processing variability of inflected forms has been accounted for by the amount of information (i.e. bits carried by the presented forms. In spite of the fact that probability distributions of inflected forms for the two paradigms differ, it was shown that the best prediction of processing variability is obtained by the probabilities derived from the predominant subparadigm which encompasses about 80% of feminine nouns. The relevance of annotated corpora in experimental psycholinguistics is discussed more in detail .
A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates
Huang, Weizhang; Kamenski, Lennard; Lang, Jens
2010-03-01
A new anisotropic mesh adaptation strategy for finite element solution of elliptic differential equations is presented. It generates anisotropic adaptive meshes as quasi-uniform ones in some metric space, with the metric tensor being computed based on hierarchical a posteriori error estimates. A global hierarchical error estimate is employed in this study to obtain reliable directional information of the solution. Instead of solving the global error problem exactly, which is costly in general, we solve it iteratively using the symmetric Gauß-Seidel method. Numerical results show that a few GS iterations are sufficient for obtaining a reasonably good approximation to the error for use in anisotropic mesh adaptation. The new method is compared with several strategies using local error estimators or recovered Hessians. Numerical results are presented for a selection of test examples and a mathematical model for heat conduction in a thermal battery with large orthotropic jumps in the material coefficients.
Minimum Mean-Square Error Single-Channel Signal Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas
2008-01-01
This topic of this thesis is MMSE signal estimation for hearing aids when only one microphone is available. The research is relevant for noise reduction systems in hearing aids. To fully benefit from the amplification provided by a hearing aid, noise reduction functionality is important as hearin...... algorithm. Although performance of the two algorithms is found comparable then the particle filter algorithm is doing a much better job tracking the noise.......-impaired persons in some noisy situations need a higher signal to noise ratio for speech to be intelligible when compared to normal-hearing persons. In this thesis two different methods to approach the MMSE signal estimation problem is examined. The methods differ in the way that models for the signal and noise...... inference is performed by particle filtering. The speech model is a time-varying auto-regressive model reparameterized by formant frequencies and bandwidths. The noise is assumed non-stationary and white. Compared to the case of using the AR coefficients directly then it is found very beneficial to perform...
Bazile , Alban; Hachem , Elie; Larroya-Huguet , Juan-Carlos; Mesri , Youssef
2018-01-01
International audience; In this work, we present a new a posteriori error estimator based on the Variational Multiscale method for anisotropic adaptive fluid mechanics problems. The general idea is to combine the large scale error based on the solved part of the solution with the sub-mesh scale error based on the unresolved part of the solution. We compute the latter with two different methods: one using the stabilizing parameters and the other using bubble functions. We propose two different...
Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous
Cohen, Emily B.; Hostelter, Jeffrey A.; Royle, J. Andrew; Marra, Peter P.
2014-01-01
Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re-encounter probabilities make interpretation problematic. We accounted for regional variation in re-encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over-wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model-derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re-encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re-encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re-encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re-encounter data to demonstrate
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Directory of Open Access Journals (Sweden)
Tomoaki Chiba
Full Text Available In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
International Nuclear Information System (INIS)
Morio, Jerome
2011-01-01
Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.
Harutyunyan, D.; Izsak, F.; van der Vegt, Jacobus J.W.; Bochev, Mikhail A.
For the adaptive solution of the Maxwell equations on three-dimensional domains with N´ed´elec edge finite element methods, we consider an implicit a posteriori error estimation technique. On each element of the tessellation an equation for the error is formulated and solved with a properly chosen
On the a priori estimation of collocation error covariance functions: a feasibility study
DEFF Research Database (Denmark)
Arabelos, D.N.; Forsberg, René; Tscherning, C.C.
2007-01-01
and the associated error covariance functions were conducted in the Arctic region north of 64 degrees latitude. The correlation between the known features of the data and the parameters variance and correlation length of the computed error covariance functions was estimated using multiple regression analysis...
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang; Alouini, Mohamed-Slim
2011-01-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over
Kelkboom, E.J.C.; Molina, G.; Kevenaar, T.A.M.; Veldhuis, Raymond N.J.; Jonker, Willem
2008-01-01
In recent years the protection of biometric data has gained increased interest from the scientific community. Methods such as the helper data system, fuzzy extractors, fuzzy vault and cancellable biometrics have been proposed for protecting biometric data. Most of these methods use cryptographic
Directory of Open Access Journals (Sweden)
Isabel C. Pérez Hoyos
2016-04-01
Full Text Available Groundwater Dependent Ecosystems (GDEs are increasingly threatened by humans’ rising demand for water resources. Consequently, it is imperative to identify the location of GDEs to protect them. This paper develops a methodology to identify the probability of an ecosystem to be groundwater dependent. Probabilities are obtained by modeling the relationship between the known locations of GDEs and factors influencing groundwater dependence, namely water table depth and climatic aridity index. Probabilities are derived for the state of Nevada, USA, using modeled water table depth and aridity index values obtained from the Global Aridity database. The model selected results from the performance comparison of classification trees (CT and random forests (RF. Based on a threshold-independent accuracy measure, RF has a better ability to generate probability estimates. Considering a threshold that minimizes the misclassification rate for each model, RF also proves to be more accurate. Regarding training accuracy, performance measures such as accuracy, sensitivity, and specificity are higher for RF. For the test set, higher values of accuracy and kappa for CT highlight the fact that these measures are greatly affected by low prevalence. As shown for RF, the choice of the cutoff probability value has important consequences on model accuracy and the overall proportion of locations where GDEs are found.
Estimating the Probabilities of Default for Callable Bonds: A Duffie-Singleton Approach
David Wang
2005-01-01
This paper presents a model for estimating the default risks implicit in the prices of callable corporate bonds. The model considers three essential ingredients in the pricing of callable corporate bonds: stochastic interest rate, default risk, and call provision. The stochastic interest rate is modeled as a square-root diffusion process. The default risk is modeled as a constant spread, with the magnitude of this spread impacting the probability of a Poisson process governing the arrival of ...
Moser , Gabriele; Zerubia , Josiane; Serpico , Sebastiano B.
2006-01-01
International audience; In remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of the pixel intensities. This paper deals with the problem of probability density function (pdf) estimation in the context of synthetic aperture radar (SAR) amplitude data analysis. Several theoretical and heuristic models for the pdfs of SAR data have been proposed in the literature, which have been proved to be effective for different land-cov...
Rahim, Ahmad Nabil Bin Ab; Mohamed, Faizal; Farid, Mohd Fairus Abdul; Fazli Zakaria, Mohd; Sangau Ligam, Alfred; Ramli, Nurhayati Binti
2018-01-01
Human factor can be affected by prevalence stress measured using Depression, Anxiety and Stress Scale (DASS). From the respondents feedback can be summarized that the main factor causes the highest prevalence stress is due to the working conditions that require operators to handle critical situation and make a prompt critical decisions. The relationship between the prevalence stress and performance shaping factors found that PSFFitness and PSFWork Process showed positive Pearson’s Correlation with the score of .763 and .826 while the level of significance, p = .028 and p = .012. These positive correlations with good significant values between prevalence stress and human performance shaping factor (PSF) related to fitness, work processes and procedures. The higher the stress level of the respondents, the higher the score of selected for the PSFs. This is due to the higher levels of stress lead to deteriorating physical health and cognitive also worsened. In addition, the lack of understanding in the work procedures can also be a factor that causes a growing stress. The higher these values will lead to the higher the probabilities of human error occur. Thus, monitoring the level of stress among operators RTP is important to ensure the safety of RTP.
The Probability of Default Under IFRS 9: Multi-period Estimation and Macroeconomic Forecast
Directory of Open Access Journals (Sweden)
Tomáš Vaněk
2017-01-01
Full Text Available In this paper we propose a straightforward, flexible and intuitive computational framework for the multi-period probability of default estimation incorporating macroeconomic forecasts. The concept is based on Markov models, the estimated economic adjustment coefficient and the official economic forecasts of the Czech National Bank. The economic forecasts are taken into account in a separate step to better distinguish between idiosyncratic and systemic risk. This approach is also attractive from the interpretational point of view. The proposed framework can be used especially when calculating lifetime expected credit losses under IFRS 9.
Hall, Eric Joseph
2016-12-08
We derive computable error estimates for finite element approximations of linear elliptic partial differential equations with rough stochastic coefficients. In this setting, the exact solutions contain high frequency content that standard a posteriori error estimates fail to capture. We propose goal-oriented estimates, based on local error indicators, for the pathwise Galerkin and expected quadrature errors committed in standard, continuous, piecewise linear finite element approximations. Derived using easily validated assumptions, these novel estimates can be computed at a relatively low cost and have applications to subsurface flow problems in geophysics where the conductivities are assumed to have lognormal distributions with low regularity. Our theory is supported by numerical experiments on test problems in one and two dimensions.
Error estimation in the neural network solution of ordinary differential equations.
Filici, Cristian
2010-06-01
In this article a method of error estimation for the neural approximation of the solution of an Ordinary Differential Equation is presented. Some examples of the application of the method support the theory presented. Copyright 2010. Published by Elsevier Ltd.
Type I Error Rates and Power Estimates of Selected Parametric and Nonparametric Tests of Scale.
Olejnik, Stephen F.; Algina, James
1987-01-01
Estimated Type I Error rates and power are reported for the Brown-Forsythe, O'Brien, Klotz, and Siegal-Tukey procedures. The effect of aligning the data using deviations from group means or group medians is investigated. (RB)
Full information estimations of a system of simultaneous equations with error component structure
Balestra, Pietro; Krishnakumar, Jaya
1987-01-01
In this paper we develop full information methods for estimating the parameters of a system of simultaneous equations with error component struc-ture and establish relationships between the various structural estimat
Salama, Paul
2008-02-01
Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.
Estimation of the common cause failure probabilities of the components under mixed testing schemes
International Nuclear Information System (INIS)
Kang, Dae Il; Hwang, Mee Jeong; Han, Sang Hoon
2009-01-01
For the case where trains or channels of standby safety systems consisting of more than two redundant components are tested in a staggered manner, the standby safety components within a train can be tested simultaneously or consecutively. In this case, mixed testing schemes, staggered and non-staggered testing schemes, are used for testing the components. Approximate formulas, based on the basic parameter method, were developed for the estimation of the common cause failure (CCF) probabilities of the components under mixed testing schemes. The developed formulas were applied to the four redundant check valves of the auxiliary feed water system as a demonstration study for their appropriateness. For a comparison, we estimated the CCF probabilities of the four redundant check valves for the mixed, staggered, and non-staggered testing schemes. The CCF probabilities of the four redundant check valves for the mixed testing schemes were estimated to be higher than those for the staggered testing scheme, and lower than those for the non-staggered testing scheme.
Estimation of probability of failure for damage-tolerant aerospace structures
Halbert, Keith
The majority of aircraft structures are designed to be damage-tolerant such that safe operation can continue in the presence of minor damage. It is necessary to schedule inspections so that minor damage can be found and repaired. It is generally not possible to perform structural inspections prior to every flight. The scheduling is traditionally accomplished through a deterministic set of methods referred to as Damage Tolerance Analysis (DTA). DTA has proven to produce safe aircraft but does not provide estimates of the probability of failure of future flights or the probability of repair of future inspections. Without these estimates maintenance costs cannot be accurately predicted. Also, estimation of failure probabilities is now a regulatory requirement for some aircraft. The set of methods concerned with the probabilistic formulation of this problem are collectively referred to as Probabilistic Damage Tolerance Analysis (PDTA). The goal of PDTA is to control the failure probability while holding maintenance costs to a reasonable level. This work focuses specifically on PDTA for fatigue cracking of metallic aircraft structures. The growth of a crack (or cracks) must be modeled using all available data and engineering knowledge. The length of a crack can be assessed only indirectly through evidence such as non-destructive inspection results, failures or lack of failures, and the observed severity of usage of the structure. The current set of industry PDTA tools are lacking in several ways: they may in some cases yield poor estimates of failure probabilities, they cannot realistically represent the variety of possible failure and maintenance scenarios, and they do not allow for model updates which incorporate observed evidence. A PDTA modeling methodology must be flexible enough to estimate accurately the failure and repair probabilities under a variety of maintenance scenarios, and be capable of incorporating observed evidence as it becomes available. This
Energy Technology Data Exchange (ETDEWEB)
Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.
2006-10-01
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
IAS 8, Accounting Policies, Changes in Accounting Estimates and Errors – A Closer Look
Muthupandian, K S
2008-01-01
The International Accounting Standards Board issued the revised version of the International Accounting Standard 8, Accounting Policies, Changes in Accounting Estimates and Errors. The objective of IAS 8 is to prescribe the criteria for selecting, applying and changing accounting policies, together with the accounting treatment and disclosure of changes in accounting policies, changes in accounting estimates and the corrections of errors. This article presents a closer look of the standard (o...
Estimation of Mechanical Signals in Induction Motors using the Recursive Prediction Error Method
DEFF Research Database (Denmark)
Børsting, H.; Knudsen, Morten; Rasmussen, Henrik
1993-01-01
Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed ........Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed .....
DEFF Research Database (Denmark)
Jensen, Jonas; Olesen, Jacob Bjerring; Stuart, Matthias Bo
2016-01-01
radius. The error sources were also studied in vivo under realistic clinical conditions, and the theoretical results were applied for correcting the volume flow errors. Twenty dialysis patients with arteriovenous fistulas were scanned to obtain vector flow maps of fistulas. When fitting an ellipsis......A method for vector velocity volume flow estimation is presented, along with an investigation of its sources of error and correction of actual volume flow measurements. Volume flow errors are quantified theoretically by numerical modeling, through flow phantom measurements, and studied in vivo...
Energy Technology Data Exchange (ETDEWEB)
Lipnikov, Konstantin [Los Alamos National Laboratory; Agouzal, Abdellatif [UNIV DE LYON; Vassilevski, Yuri [Los Alamos National Laboratory
2009-01-01
We present a new technology for generating meshes minimizing the interpolation and discretization errors or their gradients. The key element of this methodology is construction of a space metric from edge-based error estimates. For a mesh with N{sub h} triangles, the error is proportional to N{sub h}{sup -1} and the gradient of error is proportional to N{sub h}{sup -1/2} which are optimal asymptotics. The methodology is verified with numerical experiments.
Carroll, Raymond J.
2010-05-01
This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, without either instrumental variables or independence between the two samples. When the two samples are independent and the nonlinear regression model is parameterized, we propose sieve Quasi Maximum Likelihood Estimation (Q-MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification, with easily estimated standard errors. A Monte Carlo simulation and a data application are presented to show the power of the approach.
Measurement error in income and schooling, and the bias of linear estimators
DEFF Research Database (Denmark)
Bingley, Paul; Martinello, Alessandro
The characteristics of measurement error determine the bias of linear estimators. We propose a method for validating economic survey data allowing for measurement error in the validation source, and we apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data...... with Danish administrative registers. We find that measurement error in surveys is classical for annual gross income but non-classical for years of schooling, causing a 21% amplification bias in IV estimators of returns to schooling. Using a 1958 Danish schooling reform, we contextualize our result...
Uncertainty quantification in a chemical system using error estimate-based mesh adaption
International Nuclear Information System (INIS)
Mathelin, Lionel; Le Maitre, Olivier P.
2012-01-01
This paper describes a rigorous a posteriori error analysis for the stochastic solution of non-linear uncertain chemical models. The dual-based a posteriori stochastic error analysis extends the methodology developed in the deterministic finite elements context to stochastic discretization frameworks. It requires the resolution of two additional (dual) problems to yield the local error estimate. The stochastic error estimate can then be used to adapt the stochastic discretization. Different anisotropic refinement strategies are proposed, leading to a cost-efficient tool suitable for multi-dimensional problems of moderate stochastic dimension. The adaptive strategies allow both for refinement and coarsening of the stochastic discretization, as needed to satisfy a prescribed error tolerance. The adaptive strategies were successfully tested on a model for the hydrogen oxidation in supercritical conditions having 8 random parameters. The proposed methodologies are however general enough to be also applicable for a wide class of models such as uncertain fluid flows. (authors)
Huddleston, Lisa L.; Roeder, William; Merceret, Francis J.
2010-01-01
A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].
Ogawa, Takahiro; Haseyama, Miki
2013-03-01
A missing texture reconstruction method based on an error reduction (ER) algorithm, including a novel estimation scheme of Fourier transform magnitudes is presented in this brief. In our method, Fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on the ER algorithm. Specifically, by monitoring errors converged in the ER algorithm, known patches whose Fourier transform magnitudes are similar to that of the target patch are selected from the target image. In the second approach, the Fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. Consequently, by using the ER algorithm, we can estimate both the Fourier transform magnitudes and phases to reconstruct the missing areas.
International Nuclear Information System (INIS)
Mickael, M.; Gardner, R.P.; Verghese, K.
1988-01-01
An improved method for calculating the total probability of particle scattering within the solid angle subtended by finite detectors is developed, presented, and tested. The limiting polar and azimuthal angles subtended by the detector are measured from the direction that most simplifies their calculation rather than from the incident particle direction. A transformation of the particle scattering probability distribution function (pdf) is made to match the transformation of the direction from which the limiting angles are measured. The particle scattering probability to the detector is estimated by evaluating the integral of the transformed pdf over the range of the limiting angles measured from the preferred direction. A general formula for transforming the particle scattering pdf is derived from basic principles and applied to four important scattering pdf's; namely, isotropic scattering in the Lab system, isotropic neutron scattering in the center-of-mass system, thermal neutron scattering by the free gas model, and gamma-ray Klein-Nishina scattering. Some approximations have been made to these pdf's to enable analytical evaluations of the final integrals. These approximations are shown to be valid over a wide range of energies and for most elements. The particle scattering probability to spherical, planar circular, and right circular cylindrical detectors has been calculated using the new and previously reported direct approach. Results indicate that the new approach is valid and is computationally faster by orders of magnitude
Evaluation and comparison of estimation methods for failure rates and probabilities
Energy Technology Data Exchange (ETDEWEB)
Vaurio, Jussi K. [Fortum Power and Heat Oy, P.O. Box 23, 07901 Loviisa (Finland)]. E-mail: jussi.vaurio@fortum.com; Jaenkaelae, Kalle E. [Fortum Nuclear Services, P.O. Box 10, 00048 Fortum (Finland)
2006-02-01
An updated parametric robust empirical Bayes (PREB) estimation methodology is presented as an alternative to several two-stage Bayesian methods used to assimilate failure data from multiple units or plants. PREB is based on prior-moment matching and avoids multi-dimensional numerical integrations. The PREB method is presented for failure-truncated and time-truncated data. Erlangian and Poisson likelihoods with gamma prior are used for failure rate estimation, and Binomial data with beta prior are used for failure probability per demand estimation. Combined models and assessment uncertainties are accounted for. One objective is to compare several methods with numerical examples and show that PREB works as well if not better than the alternative more complex methods, especially in demanding problems of small samples, identical data and zero failures. False claims and misconceptions are straightened out, and practical applications in risk studies are presented.
Error estimation for goal-oriented spatial adaptivity for the SN equations on triangular meshes
International Nuclear Information System (INIS)
Lathouwers, D.
2011-01-01
In this paper we investigate different error estimation procedures for use within a goal oriented adaptive algorithm for the S N equations on unstructured meshes. The method is based on a dual-weighted residual approach where an appropriate adjoint problem is formulated and solved in order to obtain the importance of residual errors in the forward problem on the specific goal of interest. The forward residuals and the adjoint function are combined to obtain both economical finite element meshes tailored to the solution of the target functional as well as providing error estimates. Various approximations made to make the calculation of the adjoint angular flux more economically attractive are evaluated by comparing the performance of the resulting adaptive algorithm and the quality of the error estimators when applied to two shielding-type test problems. (author)
Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil
2011-01-01
Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.
Estimating misclassification error: a closer look at cross-validation based methods
Directory of Open Access Journals (Sweden)
Ounpraseuth Songthip
2012-11-01
Full Text Available Abstract Background To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV methods based on sampling without replacement. Monte Carlo (MC simulation studies aimed at estimating the true misclassification error conditional on the training set are commonly used to compare CV methods. We conducted an MC simulation study to compare a new method of bootstrap CV (BCV to k-fold CV for estimating clasification error. Findings For the low-dimensional conditions simulated, the modest positive bias of k-fold CV contrasted sharply with the substantial negative bias of the new BCV method. This behavior was corroborated using a real-world dataset of prognostic gene-expression profiles in breast cancer patients. Our simulation results demonstrate some extreme characteristics of variance and bias that can occur due to a fault in the design of CV exercises aimed at estimating the true conditional error of a classifier, and that appear not to have been fully appreciated in previous studies. Although CV is a sound practice for estimating a classifier’s generalization error, using CV to estimate the fixed misclassification error of a trained classifier conditional on the training set is problematic. While MC simulation of this estimation exercise can correctly represent the average bias of a classifier, it will overstate the between-run variance of the bias. Conclusions We recommend k-fold CV over the new BCV method for estimating a classifier’s generalization error. The extreme negative bias of BCV is too high a price to pay for its reduced variance.
International Nuclear Information System (INIS)
Burr, T.; Croft, S.; Krieger, T.; Martin, K.; Norman, C.; Walsh, S.
2016-01-01
One example of top-down uncertainty quantification (UQ) involves comparing two or more measurements on each of multiple items. One example of bottom-up UQ expresses a measurement result as a function of one or more input variables that have associated errors, such as a measured count rate, which individually (or collectively) can be evaluated for impact on the uncertainty in the resulting measured value. In practice, it is often found that top-down UQ exhibits larger error variances than bottom-up UQ, because some error sources are present in the fielded assay methods used in top-down UQ that are not present (or not recognized) in the assay studies used in bottom-up UQ. One would like better consistency between the two approaches in order to claim understanding of the measurement process. The purpose of this paper is to refine bottom-up uncertainty estimation by using calibration information so that if there are no unknown error sources, the refined bottom-up uncertainty estimate will agree with the top-down uncertainty estimate to within a specified tolerance. Then, in practice, if the top-down uncertainty estimate is larger than the refined bottom-up uncertainty estimate by more than the specified tolerance, there must be omitted sources of error beyond those predicted from calibration uncertainty. The paper develops a refined bottom-up uncertainty approach for four cases of simple linear calibration: (1) inverse regression with negligible error in predictors, (2) inverse regression with non-negligible error in predictors, (3) classical regression followed by inversion with negligible error in predictors, and (4) classical regression followed by inversion with non-negligible errors in predictors. Our illustrations are of general interest, but are drawn from our experience with nuclear material assay by non-destructive assay. The main example we use is gamma spectroscopy that applies the enrichment meter principle. Previous papers that ignore error in predictors
Prediction of Monte Carlo errors by a theory generalized to treat track-length estimators
International Nuclear Information System (INIS)
Booth, T.E.; Amster, H.J.
1978-01-01
Present theories for predicting expected Monte Carlo errors in neutron transport calculations apply to estimates of flux-weighted integrals sampled directly by scoring individual collisions. To treat track-length estimators, the recent theory of Amster and Djomehri is generalized to allow the score distribution functions to depend on the coordinates of two successive collisions. It has long been known that the expected track length in a region of phase space equals the expected flux integrated over that region, but that the expected statistical error of the Monte Carlo estimate of the track length is different from that of the flux integral obtained by sampling the sum of the reciprocals of the cross sections for all collisions in the region. These conclusions are shown to be implied by the generalized theory, which provides explicit equations for the expected values and errors of both types of estimators. Sampling expected contributions to the track-length estimator is also treated. Other general properties of the errors for both estimators are derived from the equations and physically interpreted. The actual values of these errors are then obtained and interpreted for a simple specific example
GonzáLez, Pablo J.; FernáNdez, José
2011-10-01
Interferometric Synthetic Aperture Radar (InSAR) is a reliable technique for measuring crustal deformation. However, despite its long application in geophysical problems, its error estimation has been largely overlooked. Currently, the largest problem with InSAR is still the atmospheric propagation errors, which is why multitemporal interferometric techniques have been successfully developed using a series of interferograms. However, none of the standard multitemporal interferometric techniques, namely PS or SB (Persistent Scatterers and Small Baselines, respectively) provide an estimate of their precision. Here, we present a method to compute reliable estimates of the precision of the deformation time series. We implement it for the SB multitemporal interferometric technique (a favorable technique for natural terrains, the most usual target of geophysical applications). We describe the method that uses a properly weighted scheme that allows us to compute estimates for all interferogram pixels, enhanced by a Montecarlo resampling technique that properly propagates the interferogram errors (variance-covariances) into the unknown parameters (estimated errors for the displacements). We apply the multitemporal error estimation method to Lanzarote Island (Canary Islands), where no active magmatic activity has been reported in the last decades. We detect deformation around Timanfaya volcano (lengthening of line-of-sight ˜ subsidence), where the last eruption in 1730-1736 occurred. Deformation closely follows the surface temperature anomalies indicating that magma crystallization (cooling and contraction) of the 300-year shallow magmatic body under Timanfaya volcano is still ongoing.
Lamb, Jennifer Y.; Waddle, J. Hardin; Qualls, Carl P.
2017-01-01
Large gaps exist in our knowledge of the ecology of stream-breeding plethodontid salamanders in the Gulf Coastal Plain. Data describing where these salamanders are likely to occur along environmental gradients, as well as their likelihood of detection, are important for the prevention and management of amphibian declines. We used presence/absence data from leaf litter bag surveys and a hierarchical Bayesian multispecies single-season occupancy model to estimate the occurrence of five species of plethodontids across reaches in headwater streams in the Gulf Coastal Plain. Average detection probabilities were high (range = 0.432–0.942) and unaffected by sampling covariates specific to the use of litter bags (i.e., bag submergence, sampling season, in-stream cover). Estimates of occurrence probabilities differed substantially between species (range = 0.092–0.703) and were influenced by the size of the upstream drainage area and by the maximum proportion of the reach that dried. The effects of these two factors were not equivalent across species. Our results demonstrate that hierarchical multispecies models successfully estimate occurrence parameters for both rare and common stream-breeding plethodontids. The resulting models clarify how species are distributed within stream networks, and they provide baseline values that will be useful in evaluating the conservation statuses of plethodontid species within lotic systems in the Gulf Coastal Plain.
A user's manual of Tools for Error Estimation of Complex Number Matrix Computation (Ver.1.0)
International Nuclear Information System (INIS)
Ichihara, Kiyoshi.
1997-03-01
'Tools for Error Estimation of Complex Number Matrix Computation' is a subroutine library which aids the users in obtaining the error ranges of the complex number linear system's solutions or the Hermitian matrices' eigen values. This library contains routines for both sequential computers and parallel computers. The subroutines for linear system error estimation calulate norms of residual vectors, matrices's condition numbers, error bounds of solutions and so on. The error estimation subroutines for Hermitian matrix eigen values' derive the error ranges of the eigen values according to the Korn-Kato's formula. This user's manual contains a brief mathematical background of error analysis on linear algebra and usage of the subroutines. (author)
International Nuclear Information System (INIS)
Esik, Olga; Tusnady, Gabor; Daubner, Kornel; Nemeth, Gyoergy; Fuezy, Marton; Szentirmay, Zoltan
1997-01-01
Purpose: The typically benign, but occasionally rapidly fatal clinical course of papillary thyroid cancer has raised the need for individual survival probability estimation, to tailor the treatment strategy exclusively to a given patient. Materials and methods: A retrospective study was performed on 400 papillary thyroid cancer patients with a median follow-up time of 7.1 years to establish a clinical database for uni- and multivariate analysis of the prognostic factors related to survival (Kaplan-Meier product limit method and Cox regression). For a more precise prognosis estimation, the effect of the most important clinical events were then investigated on the basis of a Markov renewal model. The basic concept of this approach is that each patient has an individual disease course which (besides the initial clinical categories) is affected by special events, e.g. internal covariates (local/regional/distant relapses). On the supposition that these events and the cause-specific death are influenced by the same biological processes, the parameters of transient survival probability characterizing the speed of the course of the disease for each clinical event and their sequence were determined. The individual survival curves for each patient were calculated by using these parameters and the independent significant clinical variables selected from multivariate studies, summation of which resulted in a mean cause-specific survival function valid for the entire group. On the basis of this Markov model, prediction of the cause-specific survival probability is possible for extrastudy cases, if it is supposed that the clinical events occur within new patients in the same manner and with the similar probability as within the study population. Results: The patient's age, a distant metastasis at presentation, the extent of the surgical intervention, the primary tumor size and extent (pT), the external irradiation dosage and the degree of TSH suppression proved to be
On the error estimation and T-stability of the Mann iteration
Maruster, Laura; Maruster, St.
2015-01-01
A formula of error estimation of Mann iteration is given in the case of strongly demicontractive mappings. Based on this estimation, a condition of strong convergence is obtained for the same class of mappings. T-stability for a particular case of strongly demicontractive mappings is proved. Some
The Effect of Error in Item Parameter Estimates on the Test Response Function Method of Linking.
Kaskowitz, Gary S.; De Ayala, R. J.
2001-01-01
Studied the effect of item parameter estimation for computation of linking coefficients for the test response function (TRF) linking/equating method. Simulation results showed that linking was more accurate when there was less error in the parameter estimates, and that 15 or 25 common items provided better results than 5 common items under both…
Research on the Method of Noise Error Estimation of Atomic Clocks
Song, H. J.; Dong, S. W.; Li, W.; Zhang, J. H.; Jing, Y. J.
2017-05-01
The simulation methods of different noises of atomic clocks are given. The frequency flicker noise of atomic clock is studied by using the Markov process theory. The method for estimating the maximum interval error of the frequency white noise is studied by using the Wiener process theory. Based on the operation of 9 cesium atomic clocks in the time frequency reference laboratory of NTSC (National Time Service Center), the noise coefficients of the power-law spectrum model are estimated, and the simulations are carried out according to the noise models. Finally, the maximum interval error estimates of the frequency white noises generated by the 9 cesium atomic clocks have been acquired.
Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing
2016-12-20
Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?
Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander
2016-01-01
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.
Dionisio, Kathie L; Chang, Howard H; Baxter, Lisa K
2016-11-25
Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. ZIP-code level estimates of exposure for six pollutants (CO, NO x , EC, PM 2.5 , SO 4 , O 3 ) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.
Estimation of a beam centering error in the JAERI AVF cyclotron
International Nuclear Information System (INIS)
Fukuda, M.; Okumura, S.; Arakawa, K.; Ishibori, I.; Matsumura, A.; Nakamura, N.; Nara, T.; Agematsu, T.; Tamura, H.; Karasawa, T.
1999-01-01
A method for estimating a beam centering error from a beam density distribution obtained by a single radial probe has been developed. Estimation of the centering error is based on an analysis of radial beam positions in the direction of the radial probe. Radial motion of a particle is described as betatron oscillation around an accelerated equilibrium orbit. By fitting the radial beam positions of several consecutive turns to an equation of the radial motion, not only amplitude of the centering error but also frequency of the radial betatron oscillation and energy gain per turn can be evaluated simultaneously. The estimated centering error amplitude was consistent with a result of an orbit simulation. This method was exceedingly helpful for minimizing the centering error of a 10 MeV proton beam during the early stages of acceleration. A well-centered beam was obtained by correcting the magnetic field with a first harmonic produced by two pairs of harmonic coils. In order to push back an orbit center to a magnet center, currents of the harmonic coils were optimized on the basis of the estimated centering error amplitude. (authors)
Facial motion parameter estimation and error criteria in model-based image coding
Liu, Yunhai; Yu, Lu; Yao, Qingdong
2000-04-01
Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.
Estimation of delayed neutron emission probability by using the gross theory of nuclear β-decay
International Nuclear Information System (INIS)
Tachibana, Takahiro
1999-01-01
The delayed neutron emission probabilities (P n -values) of fission products are necessary in the study of reactor physics; e.g. in the calculation of total delayed neutron yields and in the summation calculation of decay heat. In this report, the P n -values estimated by the gross theory for some fission products are compared with experiment, and it is found that, on the average, the semi-gross theory somewhat underestimates the experimental P n -values. A modification of the β-decay strength function is briefly discussed to get more reasonable P n -values. (author)
Estimating the probability of allelic drop-out of STR alleles in forensic genetics
DEFF Research Database (Denmark)
Tvedebrink, Torben; Eriksen, Poul Svante; Mogensen, Helle Smidt
2009-01-01
In crime cases with available DNA evidence, the amount of DNA is often sparse due to the setting of the crime. In such cases, allelic drop-out of one or more true alleles in STR typing is possible. We present a statistical model for estimating the per locus and overall probability of allelic drop......-out using the results of all STR loci in the case sample as reference. The methodology of logistic regression is appropriate for this analysis, and we demonstrate how to incorporate this in a forensic genetic framework....
Directory of Open Access Journals (Sweden)
Cheng-Chin Liu
2016-01-01
Full Text Available Typhoon Morakot hit southern Taiwan in 2009, bringing 48-hr of heavy rainfall [close to the Probable Maximum Precipitation (PMP] to the Tsengwen Reservoir catchment. This extreme rainfall event resulted from the combined (co-movement effect of two climate systems (i.e., typhoon and southwesterly air flow. Based on the traditional PMP estimation method (i.e., the storm transposition method, STM, two PMP estimation approaches, i.e., Amplification Index (AI and Independent System (IS approaches, which consider the combined effect are proposed in this work. The AI approach assumes that the southwesterly air flow precipitation in a typhoon event could reach its maximum value. The IS approach assumes that the typhoon and southwesterly air flow are independent weather systems. Based on these assumptions, calculation procedures for the two approaches were constructed for a case study on the Tsengwen Reservoir catchment. The results show that the PMP estimates for 6- to 60-hr durations using the two approaches are approximately 30% larger than the PMP estimates using the traditional STM without considering the combined effect. This work is a pioneer PMP estimation method that considers the combined effect of a typhoon and southwesterly air flow. Further studies on this issue are essential and encouraged.
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.
Estimation of total error in DWPF reported radionuclide inventories. Revision 1
International Nuclear Information System (INIS)
Edwards, T.B.
1995-01-01
The Defense Waste Processing Facility (DWPF) at the Savannah River Site is required to determine and report the radionuclide inventory of its glass product. For each macro-batch, the DWPF will report both the total amount (in curies) of each reportable radionuclide and the average concentration (in curies/gram of glass) of each reportable radionuclide. The DWPF is to provide the estimated error of these reported values of its radionuclide inventory as well. The objective of this document is to provide a framework for determining the estimated error in DWPF's reporting of these radionuclide inventories. This report investigates the impact of random errors due to measurement and sampling on the total amount of each reportable radionuclide in a given macro-batch. In addition, the impact of these measurement and sampling errors and process variation are evaluated to determine the uncertainty in the reported average concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch
International Nuclear Information System (INIS)
Khayat, Omid; Afarideh, Hossein; Mohammadnia, Meisam
2015-01-01
In the solid state nuclear track detectors of chemically etched type, nuclear tracks with center-to-center neighborhood of distance shorter than two times the radius of tracks will emerge as overlapping tracks. Track overlapping in this type of detectors causes tracks count losses and it becomes rather severe in high track densities. Therefore, tracks counting in this condition should include a correction factor for count losses of different tracks overlapping orders since a number of overlapping tracks may be counted as one track. Another aspect of the problem is the cases where imaging the whole area of the detector and counting all tracks are not possible. In these conditions a statistical generalization method is desired to be applicable in counting a segmented area of the detector and the results can be generalized to the whole surface of the detector. Also there is a challenge in counting the tracks in densely overlapped tracks because not sufficient geometrical or contextual information are available. It this paper we present a statistical counting method which gives the user a relation between the tracks overlapping probabilities on a segmented area of the detector surface and the total number of tracks. To apply the proposed method one can estimate the total number of tracks on a solid state detector of arbitrary shape and dimensions by approximating the tracks averaged area, whole detector surface area and some orders of tracks overlapping probabilities. It will be shown that this method is applicable in high and ultra high density tracks images and the count loss error can be enervated using a statistical generalization approach. - Highlights: • A correction factor for count losses of different tracks overlapping orders. • For the cases imaging the whole area of the detector is not possible. • Presenting a statistical generalization method for segmented areas. • Giving a relation between the tracks overlapping probabilities and the total tracks
International Nuclear Information System (INIS)
Shigeru Aoki
2005-01-01
The secondary system such as pipings, tanks and other mechanical equipment is installed in the primary system such as building. The important secondary systems should be designed to maintain their function even if they are subjected to destructive earthquake excitations. The secondary system has many nonlinear characteristics. Impact and friction characteristic, which are observed in mechanical supports and joints, are common nonlinear characteristics. As impact damper and friction damper, impact and friction characteristic are used for reduction of seismic response. In this paper, analytical methods of the first excursion probability of the secondary system with impact and friction, subjected to earthquake excitation are proposed. By using the methods, the effects of impact force, gap size and friction force on the first excursion probability are examined. When the tolerance level is normalized by the maximum response of the secondary system without impact or friction characteristics, variation of the first excursion probability is very small for various values of the natural period. In order to examine the effectiveness of the proposed method, the obtained results are compared with those obtained by the simulation method. Some estimation methods for the maximum response of the secondary system with nonlinear characteristics have been developed. (author)
Estimation of (n,f) Cross-Sections by Measuring Reaction Probability Ratios
Energy Technology Data Exchange (ETDEWEB)
Plettner, C; Ai, H; Beausang, C W; Bernstein, L A; Ahle, L; Amro, H; Babilon, M; Burke, J T; Caggiano, J A; Casten, R F; Church, J A; Cooper, J R; Crider, B; Gurdal, G; Heinz, A; McCutchan, E A; Moody, K; Punyon, J A; Qian, J; Ressler, J J; Schiller, A; Williams, E; Younes, W
2005-04-21
Neutron-induced reaction cross-sections on unstable nuclei are inherently difficult to measure due to target activity and the low intensity of neutron beams. In an alternative approach, named the 'surrogate' technique, one measures the decay probability of the same compound nucleus produced using a stable beam on a stable target to estimate the neutron-induced reaction cross-section. As an extension of the surrogate method, in this paper they introduce a new technique of measuring the fission probabilities of two different compound nuclei as a ratio, which has the advantage of removing most of the systematic uncertainties. This method was benchmarked in this report by measuring the probability of deuteron-induced fission events in coincidence with protons, and forming the ratio P({sup 236}U(d,pf))/P({sup 238}U(d,pf)), which serves as a surrogate for the known cross-section ratio of {sup 236}U(n,f)/{sup 238}U(n,f). IN addition, the P({sup 238}U(d,d{prime}f))/P({sup 236}U(d,d{prime}f)) ratio as a surrogate for the {sup 237}U(n,f)/{sup 235}U(n,f) cross-section ratio was measured for the first time in an unprecedented range of excitation energies.
Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2010-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage. In addition, the unexpected polycrystalline structure seen in the focused ion beam (FIB) cross section in the first experiment was confirmed in this experiment using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size of each card guide's tin plating to determine its finish .
International Nuclear Information System (INIS)
Hahm, Dae-Gi; Park, Kwan-Soon; Koh, Hyun-Moo
2008-01-01
The awareness of a seismic hazard and risk is being increased rapidly according to the frequent occurrences of the huge earthquakes such as the 2008 Sichuan earthquake which caused about 70,000 confirmed casualties and a 20 billion U.S. dollars economic loss. Since an earthquake load contains various uncertainties naturally, the safety of a structural system under an earthquake excitation has been assessed by probabilistic approaches. In many structural applications for a probabilistic safety assessment, it is often regarded that the failure of a system will occur when the response of the structure firstly crosses the limit barrier within a specified interval of time. The determination of such a failure probability is usually called the 'first-passage problem' and has been extensively studied during the last few decades. However, especially for the structures which show a significant nonlinear dynamic behavior, an effective and accurate method for the estimation of such a failure probability is not fully established yet. In this study, we presented a new approach to evaluate the first-passage probability of an earthquake response of seismically isolated structures. The proposed method is applied to the seismic isolation system for the containment buildings of a nuclear power plant. From the numerical example, we verified that the proposed method shows accurate results with more efficient computational efforts compared to the conventional approaches
Creel, Scott; Spong, Goran; Sands, Jennifer L; Rotella, Jay; Zeigle, Janet; Joe, Lawrence; Murphy, Kerry M; Smith, Douglas
2003-07-01
Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the 'worst-case threshold' suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a 'matching approach' to eliminate this overestimation bias.
Estimation of 3D reconstruction errors in a stereo-vision system
Belhaoua, A.; Kohler, S.; Hirsch, E.
2009-06-01
The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.
B-spline goal-oriented error estimators for geometrically nonlinear rods
2011-04-01
respectively, for the output functionals q2–q4 (linear and nonlinear with the trigonometric functions sine and cosine) in all the tests considered...of the errors resulting from the linear, quadratic and nonlinear (with trigonometric functions sine and cosine) outputs and for p = 1, 2. If the... Portugal . References [1] A.T. Adams. Sobolev Spaces. Academic Press, Boston, 1975. [2] M. Ainsworth and J.T. Oden. A posteriori error estimation in
Estimation of error in using born scaling for collision cross sections involving muonic ions
International Nuclear Information System (INIS)
Stodden, C.D.; Monkhorst, H.J.; Szalewicz, K.
1988-01-01
A quantitative estimate is obtained for the error involved in using Born scaling to calcuated excitation and ionization cross sections for collisions between muonic ions. The impact parameter version of the Born Approximation is used to calculate cross sections and Coulomb corrections for the 1s→2s excitation of αμ in collisions with d. An error of about 50% is found around the peak of the cross section curve. The error falls to less than 5% for velocities above 2 a.u
Estimation of heading gyrocompass error using a GPS 3DF system: Impact on ADCP measurements
Directory of Open Access Journals (Sweden)
Simón Ruiz
2002-12-01
Full Text Available Traditionally the horizontal orientation in a ship (heading has been obtained from a gyrocompass. This instrument is still used on research vessels but has an estimated error of about 2-3 degrees, inducing a systematic error in the cross-track velocity measured by an Acoustic Doppler Current Profiler (ADCP. The three-dimensional positioning system (GPS 3DF provides an independent heading measurement with accuracy better than 0.1 degree. The Spanish research vessel BIO Hespérides has been operating with this new system since 1996. For the first time on this vessel, the data from this new instrument are used to estimate gyrocompass error. The methodology we use follows the scheme developed by Griffiths (1994, which compares data from the gyrocompass and the GPS system in order to obtain an interpolated error function. In the present work we apply this methodology on mesoscale surveys performed during the observational phase of the OMEGA project, in the Alboran Sea. The heading-dependent gyrocompass error dominated. Errors in gyrocompass heading of 1.4-3.4 degrees have been found, which give a maximum error in measured cross-track ADCP velocity of 24 cm s-1.
Global Warming Estimation from MSU: Correction for Drift and Calibration Errors
Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Einaudi, Franco (Technical Monitor)
2000-01-01
Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have about 7am/7pm orbital geometry) and afternoon satellites (NOAA 7, 9, 11 and 14 that have about 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error. We find we can decrease the global temperature trend by about 0.07 K/decade. In addition there are systematic time dependent errors present in the data that are introduced by the drift in the satellite orbital geometry arises from the diurnal cycle in temperature which is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observations made in the MSU Ch 1 (50.3 GHz) support this approach. The error is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the errors on the global temperature trend. In one path the
Directory of Open Access Journals (Sweden)
R. Locatelli
2013-10-01
Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively. At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
International Nuclear Information System (INIS)
Carta, Jose A.; Ramirez, Penelope; Velazquez, Sergio
2008-01-01
Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error ε made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R 2 statistic (R a 2 ). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R a 2 statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R a 2 increases
Energy Technology Data Exchange (ETDEWEB)
Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Ramirez, Penelope; Velazquez, Sergio [Department of Renewable Energies, Technological Institute of the Canary Islands, Pozo Izquierdo Beach s/n, 35119 Santa Lucia, Gran Canaria, Canary Islands (Spain)
2008-10-15
Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error {epsilon} made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R{sup 2} statistic (R{sub a}{sup 2}). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R{sub a}{sup 2} statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R{sub a}{sup 2} increases. (author)
J.M. Hull; A.M. Fish; J.J. Keane; S.R. Mori; B.J Sacks; A.C. Hull
2010-01-01
One of the primary assumptions associated with many wildlife and population trend studies is that target species are correctly identified. This assumption may not always be valid, particularly for species similar in appearance to co-occurring species. We examined size overlap and identification error rates among Cooper's (Accipiter cooperii...
Estimation of probability of coastal flooding: A case study in the Norton Sound, Alaska
Kim, S.; Chapman, R. S.; Jensen, R. E.; Azleton, M. T.; Eisses, K. J.
2010-12-01
Along the Norton Sound, Alaska, coastal communities have been exposed to flooding induced by the extra-tropical storms. Lack of observation data especially with long-term variability makes it difficult to assess the probability of coastal flooding critical in planning for development and evacuation of the coastal communities. We estimated the probability of coastal flooding with the help of an existing storm surge model using ADCIRC and a wave model using WAM for the Western Alaska which includes the Norton Sound as well as the adjacent Bering Sea and Chukchi Sea. The surface pressure and winds as well as ice coverage was analyzed and put in a gridded format with 3 hour interval over the entire Alaskan Shelf by Ocean Weather Inc. (OWI) for the period between 1985 and 2009. The OWI also analyzed the surface conditions for the storm events over the 31 year time period between 1954 and 1984. The correlation between water levels recorded by NOAA tide gage and local meteorological conditions at Nome between 1992 and 2005 suggested strong local winds with prevailing Southerly components period are good proxies for high water events. We also selected heuristically the local winds with prevailing Westerly components at Shaktoolik which locates at the eastern end of the Norton Sound provided extra selection of flood events during the continuous meteorological data record between 1985 and 2009. The frequency analyses were performed using the simulated water levels and wave heights for the 56 year time period between 1954 and 2009. Different methods of estimating return periods were compared including the method according to FEMA guideline, the extreme value statistics, and fitting to the statistical distributions such as Weibull and Gumbel. The estimates are similar as expected but with a variation.
DEFF Research Database (Denmark)
Tscherning, Carl Christian
2015-01-01
outside the data area. On the other hand, a comparison of predicted quantities with observed values show that the error also varies depending on the local data standard deviation. This quantity may be (and has been) estimated using the GOCE second order vertical derivative, Tzz, in the area covered...... by the satellite. The ratio between the nearly constant standard deviations of a predicted quantity (e.g. in a 25° × 25° area) and the standard deviations of Tzz in smaller cells (e.g., 1° × 1°) have been used as a scale factor in order to obtain more realistic error estimates. This procedure has been applied...
Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition
van der Zee, Kristoffer G.
2010-10-27
A posteriori estimates of errors in quantities of interest are developed for the nonlinear system of evolution equations embodied in the Cahn-Hilliard model of binary phase transition. These involve the analysis of wellposedness of dual backward-in-time problems and the calculation of residuals. Mixed finite element approximations are developed and used to deliver numerical solutions of representative problems in one- and two-dimensional domains. Estimated errors are shown to be quite accurate in these numerical examples. © 2010 Wiley Periodicals, Inc.
Estimating the approximation error when fixing unessential factors in global sensitivity analysis
Energy Technology Data Exchange (ETDEWEB)
Sobol' , I.M. [Institute for Mathematical Modelling of the Russian Academy of Sciences, Moscow (Russian Federation); Tarantola, S. [Joint Research Centre of the European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 1, 21020 Ispra (Italy)]. E-mail: stefano.tarantola@jrc.it; Gatelli, D. [Joint Research Centre of the European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 1, 21020 Ispra (Italy)]. E-mail: debora.gatelli@jrc.it; Kucherenko, S.S. [Imperial College London (United Kingdom); Mauntz, W. [Department of Biochemical and Chemical Engineering, Dortmund University (Germany)
2007-07-15
One of the major settings of global sensitivity analysis is that of fixing non-influential factors, in order to reduce the dimensionality of a model. However, this is often done without knowing the magnitude of the approximation error being produced. This paper presents a new theorem for the estimation of the average approximation error generated when fixing a group of non-influential factors. A simple function where analytical solutions are available is used to illustrate the theorem. The numerical estimation of small sensitivity indices is discussed.
A review of some a posteriori error estimates for adaptive finite element methods
Czech Academy of Sciences Publication Activity Database
Segeth, Karel
2010-01-01
Roč. 80, č. 8 (2010), s. 1589-1600 ISSN 0378-4754. [European Seminar on Coupled Problems. Jetřichovice, 08.06.2008-13.06.2008] R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : hp-adaptive finite element method * a posteriori error estimators * computational error estimates Subject RIV: BA - General Mathematics Impact factor: 0.812, year: 2010 http://www.sciencedirect.com/science/article/pii/S0378475408004230
Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette
2009-01-01
Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.
Energy Technology Data Exchange (ETDEWEB)
Zamonsky, O M [Comision Nacional de Energia Atomica, Centro Atomico Bariloche (Argentina)
2000-07-01
The accuracy of the solutions produced by the Discrete Ordinates neutron transport nodal methods is analyzed.The obtained new numerical methodologies increase the accuracy of the analyzed scheems and give a POSTERIORI error estimators. The accuracy improvement is obtained with new equations that make the numerical procedure free of truncation errors and proposing spatial reconstructions of the angular fluxes that are more accurate than those used until present. An a POSTERIORI error estimator is rigurously obtained for one dimensional systems that, in certain type of problems, allows to quantify the accuracy of the solutions. From comparisons with the one dimensional results, an a POSTERIORI error estimator is also obtained for multidimensional systems. LOCAL indicators, which quantify the spatial distribution of the errors, are obtained by the decomposition of the menctioned estimators. This makes the proposed methodology suitable to perform adaptive calculations. Some numerical examples are presented to validate the theoretical developements and to illustrate the ranges where the proposed approximations are valid.
Munsinger, H
1977-01-01
Published studies show that among identical twins, lower birthweight is associated with lower adult intelligence. However, no such relation between birthweight and adult IQ exists among fraternal twins. A likely explanation for the association between birthweight and intelligence among identical twins is the identical twin transfusion syndrome which occurs only between some monochorionic identical twin pairs. The IQ scores from separated identical twins were reanalysed to explore the consequences of identical twin transfusion syndrome for IQ resemblance and heritability. Among 129 published cases of identical twin pairs reared apart, 76 pairs contained some birthweight information. The 76 pairs were separated into three classes: 23 pairs in which there was clear evidence of a substantial birthweight differences (indicating the probable existence of the identical twin transfusion syndrome), 27 pairs in which the information on birthweight was ambiguous (?), and 26 pairs in which there was clear evidence that the twins were similar in birthweight. The reanalyses showed: (1) birthweight differences are positively associated with IQ differences in the total sample of separated identical twins; (2) within the group of 23 twin pairs who showed large birthweight differences, there was a positive relation between birthweight differences and IQ differences; (3) when heritability of IQ is estimated for those twins who do not suffer large birthweight differences, the resemblance (and thus, h2/b) of the separated identical twins' IG is 0-95. Given that the average reliability of the individual IQ test is around 0-95, these data suggest that genetic factors and errors of measurement cause the individual differences in IQ among human beings. Because of the identical twin transfusion syndrome, previous studies of MZ twins have underestimated the effect of genetic factors on IQ. An analysis of the IQs for heavier and lighter birthweight twins suggests that the main effect of the
Boeschoten, Laura; Oberski, Daniel; De Waal, Ton
2017-01-01
Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible
Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation
International Nuclear Information System (INIS)
Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.
2016-01-01
In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also
Doss, Hani; Tan, Aixin
2014-09-01
In the classical biased sampling problem, we have k densities π 1 (·), …, π k (·), each known up to a normalizing constant, i.e. for l = 1, …, k , π l (·) = ν l (·)/ m l , where ν l (·) is a known function and m l is an unknown constant. For each l , we have an iid sample from π l , · and the problem is to estimate the ratios m l /m s for all l and all s . This problem arises frequently in several situations in both frequentist and Bayesian inference. An estimate of the ratios was developed and studied by Vardi and his co-workers over two decades ago, and there has been much subsequent work on this problem from many different perspectives. In spite of this, there are no rigorous results in the literature on how to estimate the standard error of the estimate. We present a class of estimates of the ratios of normalizing constants that are appropriate for the case where the samples from the π l 's are not necessarily iid sequences, but are Markov chains. We also develop an approach based on regenerative simulation for obtaining standard errors for the estimates of ratios of normalizing constants. These standard error estimates are valid for both the iid case and the Markov chain case.
Directory of Open Access Journals (Sweden)
Vanessa M Adams
Full Text Available The need to integrate social and economic factors into conservation planning has become a focus of academic discussions and has important practical implications for the implementation of conservation areas, both private and public. We conducted a survey in the Daly Catchment, Northern Territory, to inform the design and implementation of a stewardship payment program. We used a choice model to estimate the likely level of participation in two legal arrangements--conservation covenants and management agreements--based on payment level and proportion of properties required to be managed. We then spatially predicted landholders' probability of participating at the resolution of individual properties and incorporated these predictions into conservation planning software to examine the potential for the stewardship program to meet conservation objectives. We found that the properties that were least costly, per unit area, to manage were also the least likely to participate. This highlights a tension between planning for a cost-effective program and planning for a program that targets properties with the highest probability of participation.
Estimation of the nuclear fuel assembly eigenfrequencies in the probability sense
Directory of Open Access Journals (Sweden)
Zeman V.
2014-12-01
Full Text Available The paper deals with upper and lower limits estimation of the nuclear fuel assembly eigenfrequencies, whose design and operation parameters are random variables. Each parameter is defined by its mean value and standard deviation or by a range of values. The gradient and three sigma criterion approach is applied to the calculation of the upper and lower limits of fuel assembly eigenfrequencies in the probability sense. Presented analytical approach used for the calculation of eigenfrequencies sensitivity is based on the modal synthesis method and the fuel assembly decomposition into six identical revolved fuel rod segments, centre tube and load-bearing skeleton linked by spacer grids. The method is applied for the Russian TVSA-T fuel assembly in the WWER1000/320 type reactor core in the Czech nuclear power plant Temelín.
Wenger, Seth J; Freeman, Mary C
2008-10-01
Researchers have developed methods to account for imperfect detection of species with either occupancy (presence absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.
An Estimation of a Passive Infra-Red Sensor Probability of Detection
International Nuclear Information System (INIS)
Osman, E.A.; El-Gazar, M.I.; Shaat, M.K.; El-Kafas, A.A.; Zidan, W.I.; Wadoud, A.A.
2009-01-01
Passive Infera-Red (PIR) sensors are one of many detection sensors are used to detect any intrusion process of the nuclear sites. In this work, an estimation of a PIR Sensor's Probability of Detection of a hypothetical facility is presented. sensor performance testing performed to determine whether a particular sensor will be acceptable in a proposed design. We have access to a sensor test field in which the sensor of interest is already properly installed and the parameters have been set to optimal levels by preliminary testing. The PIR sensor construction, operation and design for the investigated nuclear site are explained. Walking and running intrusion tests were carried out inside the field areas of the PIR sensor to evaluate the sensor performance during the intrusion process. 10 trials experimentally performed for achieving the intrusion process via a passive infra-red sensor's network system. The performance and intrusion senses of PIR sensors inside the internal zones was recorded and evaluated.
Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics
DEFF Research Database (Denmark)
Holland, Dominic; Wang, Yunpeng; Thompson, Wesley K
2016-01-01
Genome-wide Association Studies (GWAS) result in millions of summary statistics ("z-scores") for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric......-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities, relying only on summary statistics from GWAS substudies, and a scheme allowing...... for estimating the degree of polygenicity of the phenotype and predicting the proportion of chip heritability explainable by genome-wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N = 82,315) and putamen volume (N = 12,596), with approximately...
A novel multitemporal insar model for joint estimation of deformation rates and orbital errors
Zhang, Lei
2014-06-01
Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference. © 2013 IEEE.
Fottrell, Edward; Byass, Peter; Berhane, Yemane
2008-03-25
As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of
Directory of Open Access Journals (Sweden)
Berhane Yemane
2008-03-01
estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang
2011-10-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over uncorrelated Rayleigh fading channels. We first derive the ergodic (average) capacity expressions for such systems when power adaptation is applied at the transmitter. The exact capacity expression for the uniform power allocation case is also presented. Furthermore, to investigate the diversity order of MIMO MRT-MRC scheme, we derive the BER performance under a uniform power allocation policy. We also present an asymptotic BER performance analysis for the MIMO MRT-MRC system with multiuser diversity. The numerical results are given to illustrate the sensitivity of the main performance to the channel estimation error and the tightness of the approximate cutoff value. © 2011 IEEE.
Directory of Open Access Journals (Sweden)
Khasanov Zimfir
2018-01-01
Full Text Available The article reviews the capabilities and particularities of the approach to the improvement of metrological characteristics of fiber-optic pressure sensors (FOPS based on estimation estimation of dynamic errors in laser optoelectronic dimension gauges for geometric measurement of details. It is shown that the proposed criteria render new methods for conjugation of optoelectronic converters in the dimension gauge for geometric measurements in order to reduce the speed and volume requirements for the Random Access Memory (RAM of the video controller which process the signal. It is found that the lower relative error, the higher the interrogetion speed of the CCD array. It is shown that thus, the maximum achievable dynamic accuracy characteristics of the optoelectronic gauge are determined by the following conditions: the parameter stability of the electronic circuits in the CCD array and the microprocessor calculator; linearity of characteristics; error dynamics and noise in all electronic circuits of the CCD array and microprocessor calculator.
Impact of Channel Estimation Errors on Multiuser Detection via the Replica Method
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Li Husheng
2005-01-01
Full Text Available For practical wireless DS-CDMA systems, channel estimation is imperfect due to noise and interference. In this paper, the impact of channel estimation errors on multiuser detection (MUD is analyzed under the framework of the replica method. System performance is obtained in the large system limit for optimal MUD, linear MUD, and turbo MUD, and is validated by numerical results for finite systems.
Some error estimates for the lumped mass finite element method for a parabolic problem
Chatzipantelidis, P.
2012-01-01
We study the spatially semidiscrete lumped mass method for the model homogeneous heat equation with homogeneous Dirichlet boundary conditions. Improving earlier results we show that known optimal order smooth initial data error estimates for the standard Galerkin method carry over to the lumped mass method whereas nonsmooth initial data estimates require special assumptions on the triangulation. We also discuss the application to time discretization by the backward Euler and Crank-Nicolson methods. © 2011 American Mathematical Society.
Directory of Open Access Journals (Sweden)
Sarah Ehlers
2018-04-01
Full Text Available Today, non-expensive remote sensing (RS data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.
Dreano, Denis; Tandeo, P.; Pulido, M.; Ait-El-Fquih, Boujemaa; Chonavel, T.; Hoteit, Ibrahim
2017-01-01
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended
International Nuclear Information System (INIS)
Vasil'ev, A.P.; Krepkij, A.S.; Lukin, A.V.; Mikhal'kova, A.G.; Orlov, A.I.; Perezhogin, V.D.; Samojlova, L.Yu.; Sokolov, Yu.A.; Terekhin, V.A.; Chernukhin, Yu.I.
1991-01-01
Critical mass experiments were performed using assemblies which simulated one-dimensional lattice consisting of shielding containers with metal fissile materials. Calculations of the criticality of the above assemblies were carried out using the KLAN program with the BAS neutron constants. Errors in the calculations of the criticality for one-, two-, and three-dimensional lattices are estimated. 3 refs.; 1 tab
Error Estimates for a Semidiscrete Finite Element Method for Fractional Order Parabolic Equations
Jin, Bangti; Lazarov, Raytcho; Zhou, Zhi
2013-01-01
initial data, i.e., ν ∈ H2(Ω) ∩ H0 1(Ω) and ν ∈ L2(Ω). For the lumped mass method, the optimal L2-norm error estimate is valid only under an additional assumption on the mesh, which in two dimensions is known to be satisfied for symmetric meshes. Finally
A novel multitemporal insar model for joint estimation of deformation rates and orbital errors
Zhang, Lei; Ding, Xiaoli; Lu, Zhong; Jung, Hyungsup; Hu, Jun; Feng, Guangcai
2014-01-01
be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long
L∞-error estimates of a finite element method for the Hamilton-Jacobi-Bellman equations
International Nuclear Information System (INIS)
Bouldbrachene, M.
1994-11-01
We study the finite element approximation for the solution of the Hamilton-Jacobi-Bellman equations involving a system of quasi-variational inequalities (QVI). We also give the optimal L ∞ -error estimates, using the concepts of subsolutions and discrete regularity. (author). 7 refs
An error bound estimate and convergence of the Nodal-LTS N solution in a rectangle
International Nuclear Information System (INIS)
Hauser, Eliete Biasotto; Pazos, Ruben Panta; Tullio de Vilhena, Marco
2005-01-01
In this work, we report the mathematical analysis concerning error bound estimate and convergence of the Nodal-LTS N solution in a rectangle. For such we present an efficient algorithm, called LTS N 2D-Diag solution for Cartesian geometry
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www. science direct.com/ science /article/pii/S0377042716301492?via%3Dihub
Partial-Interval Estimation of Count: Uncorrected and Poisson-Corrected Error Levels
Yoder, Paul J.; Ledford, Jennifer R.; Harbison, Amy L.; Tapp, Jon T.
2018-01-01
A simulation study that used 3,000 computer-generated event streams with known behavior rates, interval durations, and session durations was conducted to test whether the main and interaction effects of true rate and interval duration affect the error level of uncorrected and Poisson-transformed (i.e., "corrected") count as estimated by…
Estimation of chromatic errors from broadband images for high contrast imaging
Sirbu, Dan; Belikov, Ruslan
2015-09-01
Usage of an internal coronagraph with an adaptive optical system for wavefront correction for direct imaging of exoplanets is currently being considered for many mission concepts, including as an instrument addition to the WFIRST-AFTA mission to follow the James Web Space Telescope. The main technical challenge associated with direct imaging of exoplanets with an internal coronagraph is to effectively control both the diffraction and scattered light from the star so that the dim planetary companion can be seen. For the deformable mirror (DM) to recover a dark hole region with sufficiently high contrast in the image plane, wavefront errors are usually estimated using probes on the DM. To date, most broadband lab demonstrations use narrowband filters to estimate the chromaticity of the wavefront error, but this reduces the photon flux per filter and requires a filter system. Here, we propose a method to estimate the chromaticity of wavefront errors using only a broadband image. This is achieved by using special DM probes that have sufficient chromatic diversity. As a case example, we simulate the retrieval of the spectrum of the central wavelength from broadband images for a simple shaped- pupil coronagraph with a conjugate DM and compute the resulting estimation error.
L∞-error estimate for a system of elliptic quasivariational inequalities
Directory of Open Access Journals (Sweden)
M. Boulbrachene
2003-01-01
Full Text Available We deal with the numerical analysis of a system of elliptic quasivariational inequalities (QVIs. Under W2,p(Ω-regularity of the continuous solution, a quasi-optimal L∞-convergence of a piecewise linear finite element method is established, involving a monotone algorithm of Bensoussan-Lions type and standard uniform error estimates known for elliptic variational inequalities (VIs.
Some examples of the estimation of error for calorimetric assay of plutonium-bearing solids
International Nuclear Information System (INIS)
Rodenburg, W.W.
1977-04-01
This report provides numerical examples of error estimation and related measurement assurance programs for the calorimetric assay of plutonium. It is primarily intended for users who do not consider themselves experts in the field of calorimetry. These examples will provide practical and useful information in establishing a calorimetric assay capability which fulfills regulatory requirements. 10 tables, 5 figures
A Generalizability Theory Approach to Standard Error Estimates for Bookmark Standard Settings
Lee, Guemin; Lewis, Daniel M.
2008-01-01
The bookmark standard-setting procedure is an item response theory-based method that is widely implemented in state testing programs. This study estimates standard errors for cut scores resulting from bookmark standard settings under a generalizability theory model and investigates the effects of different universes of generalization and error…
Statistical error estimation of the Feynman-α method using the bootstrap method
International Nuclear Information System (INIS)
Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho
2016-01-01
Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)
A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series
Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.
2011-01-01
Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…
Can i just check...? Effects of edit check questions on measurement error and survey estimates
Lugtig, Peter; Jäckle, Annette
2014-01-01
Household income is difficult to measure, since it requires the collection of information about all potential income sources for each member of a household.Weassess the effects of two types of edit check questions on measurement error and survey estimates: within-wave edit checks use responses to
On Estimation of the A-norm of the Error in CG and PCG
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2003-01-01
Roč. 3, - (2003), s. 553-554 ISSN 1617-7061. [GAMM. Padua, 24.03.2003-28.03.2003] R&D Projects: GA ČR GA201/02/0595 Institutional research plan: CEZ:AV0Z1030915 Keywords : preconditioned conjugate gradient * error estimates * stopping criteria Subject RIV: BA - General Mathematics
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www.sciencedirect.com/science/article/pii/S0377042716301492?via%3Dihub
Estimating the annotation error rate of curated GO database sequence annotations
Directory of Open Access Journals (Sweden)
Brown Alfred L
2007-05-01
Full Text Available Abstract Background Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO sequence database (GOSeqLite. This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. Results We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006 at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS had an estimated error rate of 49%. Conclusion While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.
Jones, Reese E.; Mandadapu, Kranthi K.
2012-04-01
We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.
Using cell phone location to assess misclassification errors in air pollution exposure estimation.
Yu, Haofei; Russell, Armistead; Mulholland, James; Huang, Zhijiong
2018-02-01
Air pollution epidemiologic and health impact studies often rely on home addresses to estimate individual subject's pollution exposure. In this study, we used detailed cell phone location data, the call detail record (CDR), to account for the impact of spatiotemporal subject mobility on estimates of ambient air pollutant exposure. This approach was applied on a sample with 9886 unique simcard IDs in Shenzhen, China, on one mid-week day in October 2013. Hourly ambient concentrations of six chosen pollutants were simulated by the Community Multi-scale Air Quality model fused with observational data, and matched with detailed location data for these IDs. The results were compared with exposure estimates using home addresses to assess potential exposure misclassification errors. We found the misclassifications errors are likely to be substantial when home location alone is applied. The CDR based approach indicates that the home based approach tends to over-estimate exposures for subjects with higher exposure levels and under-estimate exposures for those with lower exposure levels. Our results show that the cell phone location based approach can be used to assess exposure misclassification error and has the potential for improving exposure estimates in air pollution epidemiology studies. Copyright © 2017 Elsevier Ltd. All rights reserved.
Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty
Ballantyne, A. P.; Andres, R.; Houghton, R.; Stocker, B. D.; Wanninkhof, R.; Anderegg, W.; Cooper, L. A.; DeGrandpre, M.; Tans, P. P.; Miller, J. B.; Alden, C.; White, J. W. C.
2015-04-01
Over the last 5 decades monitoring systems have been developed to detect changes in the accumulation of carbon (C) in the atmosphere and ocean; however, our ability to detect changes in the behavior of the global C cycle is still hindered by measurement and estimate errors. Here we present a rigorous and flexible framework for assessing the temporal and spatial components of estimate errors and their impact on uncertainty in net C uptake by the biosphere. We present a novel approach for incorporating temporally correlated random error into the error structure of emission estimates. Based on this approach, we conclude that the 2σ uncertainties of the atmospheric growth rate have decreased from 1.2 Pg C yr-1 in the 1960s to 0.3 Pg C yr-1 in the 2000s due to an expansion of the atmospheric observation network. The 2σ uncertainties in fossil fuel emissions have increased from 0.3 Pg C yr-1 in the 1960s to almost 1.0 Pg C yr-1 during the 2000s due to differences in national reporting errors and differences in energy inventories. Lastly, while land use emissions have remained fairly constant, their errors still remain high and thus their global C uptake uncertainty is not trivial. Currently, the absolute errors in fossil fuel emissions rival the total emissions from land use, highlighting the extent to which fossil fuels dominate the global C budget. Because errors in the atmospheric growth rate have decreased faster than errors in total emissions have increased, a ~20% reduction in the overall uncertainty of net C global uptake has occurred. Given all the major sources of error in the global C budget that we could identify, we are 93% confident that terrestrial C uptake has increased and 97% confident that ocean C uptake has increased over the last 5 decades. Thus, it is clear that arguably one of the most vital ecosystem services currently provided by the biosphere is the continued removal of approximately half of atmospheric CO2 emissions from the atmosphere
Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.
Carroll, Raymond J.
2011-03-01
In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.
International Nuclear Information System (INIS)
Guikema, Seth D.
2007-01-01
Priors play an important role in the use of Bayesian methods in risk analysis, and using all available information to formulate an informative prior can lead to more accurate posterior inferences. This paper examines the practical implications of using five different methods for formulating an informative prior for a failure probability based on past data. These methods are the method of moments, maximum likelihood (ML) estimation, maximum entropy estimation, starting from a non-informative 'pre-prior', and fitting a prior based on confidence/credible interval matching. The priors resulting from the use of these different methods are compared qualitatively, and the posteriors are compared quantitatively based on a number of different scenarios of observed data used to update the priors. The results show that the amount of information assumed in the prior makes a critical difference in the accuracy of the posterior inferences. For situations in which the data used to formulate the informative prior is an accurate reflection of the data that is later observed, the ML approach yields the minimum variance posterior. However, the maximum entropy approach is more robust to differences between the data used to formulate the prior and the observed data because it maximizes the uncertainty in the prior subject to the constraints imposed by the past data
Lugtig, Peter; Toepoel, Vera
2016-01-01
Respondents in an Internet panel survey can often choose which device they use to complete questionnaires: a traditional PC, laptop, tablet computer, or a smartphone. Because all these devices have different screen sizes and modes of data entry, measurement errors may differ between devices. Using
Estimation of sampling error uncertainties in observed surface air temperature change in China
Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun
2017-08-01
This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.
ERROR BOUNDS FOR SURFACE AREA ESTIMATORS BASED ON CROFTON’S FORMULA
Directory of Open Access Journals (Sweden)
Markus Kiderlen
2011-05-01
Full Text Available According to Crofton's formula, the surface area S(A of a sufficiently regular compact set A in Rd is proportional to the mean of all total projections pA (u on a linear hyperplane with normal u, uniformly averaged over all unit vectors u. In applications, pA (u is only measured in k directions and the mean is approximated by a finite weighted sum bS(A of the total projections in these directions. The choice of the weights depends on the selected quadrature rule. We define an associated zonotope Z (depending only on the projection directions and the quadrature rule, and show that the relative error bS (A/S (A is bounded from below by the inradius of Z and from above by the circumradius of Z. Applying a strengthened isoperimetric inequality due to Bonnesen, we show that the rectangular quadrature rule does not give the best possible error bounds for d =2. In addition, we derive asymptotic behavior of the error (with increasing k in the planar case. The paper concludes with applications to surface area estimation in design-based digital stereology where we show that the weights due to Bonnesen's inequality are better than the usual weights based on the rectangular rule and almost optimal in the sense that the relative error of the surface area estimator is very close to the minimal error.
Eilers, Anna-Christina; Hennawi, Joseph F.; Lee, Khee-Gan
2017-08-01
We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Lyα forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear principal component analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation γ -1, while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method recovers the underlying quasar continua to a precision of ≃ 7 % and ≃ 10 % at z = 3 and z = 5, respectively. Given the number of principal component spectra, this is comparable to the underlying accuracy of the PCA model itself. Most importantly, we show that we can achieve a nearly unbiased estimate of the slope γ -1 of the IGM temperature-density relation with a precision of +/- 8.6 % at z = 3 and +/- 6.1 % at z = 5, for an ensemble of ten mock high-resolution quasar spectra. Applying this method to real quasar spectra and comparing to a more realistic IGM model from hydrodynamical simulations would enable precise measurements of the thermal and cosmological parameters governing the IGM, albeit with somewhat larger uncertainties, given the increased flexibility of the model.
Influence of the statistical distribution of bioassay measurement errors on the intake estimation
International Nuclear Information System (INIS)
Lee, T. Y; Kim, J. K
2006-01-01
The purpose of this study is to provide the guidance necessary for making a selection of error distributions by analyzing influence of statistical distribution for a type of bioassay measurement error on the intake estimation. For this purpose, intakes were estimated using maximum likelihood method for cases that error distributions are normal and lognormal, and comparisons between two distributions for the estimated intakes were made. According to the results of this study, in case that measurement results for lung retention are somewhat greater than the limit of detection it appeared that distribution types have negligible influence on the results. Whereas in case of measurement results for the daily excretion rate, the results obtained from assumption of a lognormal distribution were 10% higher than those obtained from assumption of a normal distribution. In view of these facts, in case where uncertainty component is governed by counting statistics it is considered that distribution type have no influence on intake estimation. Whereas in case where the others are predominant, it is concluded that it is clearly desirable to estimate the intake assuming a lognormal distribution
Accurate and fast methods to estimate the population mutation rate from error prone sequences
Directory of Open Access Journals (Sweden)
Miyamoto Michael M
2009-08-01
Full Text Available Abstract Background The population mutation rate (θ remains one of the most fundamental parameters in genetics, ecology, and evolutionary biology. However, its accurate estimation can be seriously compromised when working with error prone data such as expressed sequence tags, low coverage draft sequences, and other such unfinished products. This study is premised on the simple idea that a random sequence error due to a chance accident during data collection or recording will be distributed within a population dataset as a singleton (i.e., as a polymorphic site where one sampled sequence exhibits a unique base relative to the common nucleotide of the others. Thus, one can avoid these random errors by ignoring the singletons within a dataset. Results This strategy is implemented under an infinite sites model that focuses on only the internal branches of the sample genealogy where a shared polymorphism can arise (i.e., a variable site where each alternative base is represented by at least two sequences. This approach is first used to derive independently the same new Watterson and Tajima estimators of θ, as recently reported by Achaz 1 for error prone sequences. It is then used to modify the recent, full, maximum-likelihood model of Knudsen and Miyamoto 2, which incorporates various factors for experimental error and design with those for coalescence and mutation. These new methods are all accurate and fast according to evolutionary simulations and analyses of a real complex population dataset for the California seahare. Conclusion In light of these results, we recommend the use of these three new methods for the determination of θ from error prone sequences. In particular, we advocate the new maximum likelihood model as a starting point for the further development of more complex coalescent/mutation models that also account for experimental error and design.
Test models for improving filtering with model errors through stochastic parameter estimation
International Nuclear Information System (INIS)
Gershgorin, B.; Harlim, J.; Majda, A.J.
2010-01-01
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
Error Estimates for Approximate Solutions of the Riccati Equation with Real or Complex Potentials
Finster, Felix; Smoller, Joel
2010-09-01
A method is presented for obtaining rigorous error estimates for approximate solutions of the Riccati equation, with real or complex potentials. Our main tool is to derive invariant region estimates for complex solutions of the Riccati equation. We explain the general strategy for applying these estimates and illustrate the method in typical examples, where the approximate solutions are obtained by gluing together WKB and Airy solutions of corresponding one-dimensional Schrödinger equations. Our method is motivated by, and has applications to, the analysis of linear wave equations in the geometry of a rotating black hole.
Energy Technology Data Exchange (ETDEWEB)
Kunin, Victor; Engelbrektson, Anna; Ochman, Howard; Hugenholtz, Philip
2009-08-01
Massively parallel pyrosequencing of the small subunit (16S) ribosomal RNA gene has revealed that the extent of rare microbial populations in several environments, the 'rare biosphere', is orders of magnitude higher than previously thought. One important caveat with this method is that sequencing error could artificially inflate diversity estimates. Although the per-base error of 16S rDNA amplicon pyrosequencing has been shown to be as good as or lower than Sanger sequencing, no direct assessments of pyrosequencing errors on diversity estimates have been reported. Using only Escherichia coli MG1655 as a reference template, we find that 16S rDNA diversity is grossly overestimated unless relatively stringent read quality filtering and low clustering thresholds are applied. In particular, the common practice of removing reads with unresolved bases and anomalous read lengths is insufficient to ensure accurate estimates of microbial diversity. Furthermore, common and reproducible homopolymer length errors can result in relatively abundant spurious phylotypes further confounding data interpretation. We suggest that stringent quality-based trimming of 16S pyrotags and clustering thresholds no greater than 97% identity should be used to avoid overestimates of the rare biosphere.
Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata
Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.
2012-01-01
Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).
Accuracy and Sources of Error for an Angle Independent Volume Flow Estimator
DEFF Research Database (Denmark)
Jensen, Jonas; Olesen, Jacob Bjerring; Hansen, Peter Møller
2014-01-01
This paper investigates sources of error for a vector velocity volume flow estimator. Quantification of the estima tor’s accuracy is performed theoretically and investigated in vivo . Womersley’s model for pulsatile flow is used to simulate velo city profiles and calculate volume flow errors....... A BK Medical UltraView 800 ultrasound scanner with a 9 MHz linear array transducer is used to obtain Vector Flow Imaging sequences of a superficial part of the fistulas. Cross-sectional diameters of each fistu la are measured on B-mode images by rotating the scan plane 90 degrees. The major axis...
Estimation of the wind turbine yaw error by support vector machines
DEFF Research Database (Denmark)
Sheibat-Othman, Nida; Othman, Sami; Tayari, Raoaa
2015-01-01
Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology...... is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators...
Directory of Open Access Journals (Sweden)
Kim Hyang-Mi
2012-09-01
Full Text Available Abstract Background In epidemiological studies, it is often not possible to measure accurately exposures of participants even if their response variable can be measured without error. When there are several groups of subjects, occupational epidemiologists employ group-based strategy (GBS for exposure assessment to reduce bias due to measurement errors: individuals of a group/job within study sample are assigned commonly to the sample mean of exposure measurements from their group in evaluating the effect of exposure on the response. Therefore, exposure is estimated on an ecological level while health outcomes are ascertained for each subject. Such study design leads to negligible bias in risk estimates when group means are estimated from ‘large’ samples. However, in many cases, only a small number of observations are available to estimate the group means, and this causes bias in the observed exposure-disease association. Also, the analysis in a semi-ecological design may involve exposure data with the majority missing and the rest observed with measurement errors and complete response data collected with ascertainment. Methods In workplaces groups/jobs are naturally ordered and this could be incorporated in estimation procedure by constrained estimation methods together with the expectation and maximization (EM algorithms for regression models having measurement error and missing values. Four methods were compared by a simulation study: naive complete-case analysis, GBS, the constrained GBS (CGBS, and the constrained expectation and maximization (CEM. We illustrated the methods in the analysis of decline in lung function due to exposures to carbon black. Results Naive and GBS approaches were shown to be inadequate when the number of exposure measurements is too small to accurately estimate group means. The CEM method appears to be best among them when within each exposure group at least a ’moderate’ number of individuals have their
Errors in the estimation method for the rejection of vibrations in adaptive optics systems
Kania, Dariusz
2017-06-01
In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.
A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation
Directory of Open Access Journals (Sweden)
Tianshuang Qiu
2007-12-01
Full Text Available This paper proposes a geometric method to locate a mobile station (MS in a mobile cellular network when both the range and angle measurements are corrupted by non-line-of-sight (NLOS errors. The MS location is restricted to an enclosed region by geometric constraints from the temporal-spatial characteristics of the radio propagation channel. A closed-form equation of the MS position, time of arrival (TOA, angle of arrival (AOA, and angle spread is provided. The solution space of the equation is very large because the angle spreads are random variables in nature. A constrained objective function is constructed to further limit the MS position. A Lagrange multiplier-based solution and a numerical solution are proposed to resolve the MS position. The estimation quality of the estimator in term of Ã¢Â€ÂœbiasedÃ¢Â€Â or Ã¢Â€ÂœunbiasedÃ¢Â€Â is discussed. The scale factors, which may be used to evaluate NLOS propagation level, can be estimated by the proposed method. AOA seen at base stations may be corrected to some degree. The performance comparisons among the proposed method and other hybrid location methods are investigated on different NLOS error models and with two scenarios of cell layout. It is found that the proposed method can deal with NLOS error effectively, and it is attractive for location estimation in cellular networks.
Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
Directory of Open Access Journals (Sweden)
Andreas Josefsson
2012-01-01
Full Text Available Frequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noise and some form of averaging is needed in order to obtain a consistent estimator. With Welch's method, the discrete Fourier transform is used and the data is segmented into smaller blocks so that averaging can be performed when estimating the spectrum. However, this segmentation introduces leakage effects. As a result, the estimated frequency response function suffers from both systematic (bias and random errors due to leakage. In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. The method is based on using a sum of real exponentials to describe the window's deterministic autocorrelation function. Simple expressions are derived for a rectangular window and a Hanning window. The theoretical expressions are verified with numerical simulations and a very good agreement is found between the results from the proposed bias expressions and the empirical results.
International Nuclear Information System (INIS)
Yu Watanabe; Masahito Ueda
2012-01-01
Full text: When we try to obtain information about a quantum system, we need to perform measurement on the system. The measurement process causes unavoidable state change. Heisenberg discussed a thought experiment of the position measurement of a particle by using a gamma-ray microscope, and found a trade-off relation between the error of the measured position and the disturbance in the momentum caused by the measurement process. The trade-off relation epitomizes the complementarity in quantum measurements: we cannot perform a measurement of an observable without causing disturbance in its canonically conjugate observable. However, at the time Heisenberg found the complementarity, quantum measurement theory was not established yet, and Kennard and Robertson's inequality erroneously interpreted as a mathematical formulation of the complementarity. Kennard and Robertson's inequality actually implies the indeterminacy of the quantum state: non-commuting observables cannot have definite values simultaneously. However, Kennard and Robertson's inequality reflects the inherent nature of a quantum state alone, and does not concern any trade-off relation between the error and disturbance in the measurement process. In this talk, we report a resolution to the complementarity in quantum measurements. First, we find that it is necessary to involve the estimation process from the outcome of the measurement for quantifying the error and disturbance in the quantum measurement. We clarify the implicitly involved estimation process in Heisenberg's gamma-ray microscope and other measurement schemes, and formulate the error and disturbance for an arbitrary quantum measurement by using quantum estimation theory. The error and disturbance are defined in terms of the Fisher information, which gives the upper bound of the accuracy of the estimation. Second, we obtain uncertainty relations between the measurement errors of two observables [1], and between the error and disturbance in the
Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization
Casas, R.; Marco, A.; Guerrero, J. J.; Falcó, J.
2006-12-01
Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.
Over, Thomas M.; Saito, Riki J.; Veilleux, Andrea G.; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey L.
2016-06-28
This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged
Directory of Open Access Journals (Sweden)
Leszek Klukowski
2012-01-01
Full Text Available This paper presents a review of results of the author in the area of estimation of the relations of equivalence, tolerance and preference within a finite set based on multiple, independent (in a stochastic way pairwise comparisons with random errors, in binary and multivalent forms. These estimators require weaker assumptions than those used in the literature on the subject. Estimates of the relations are obtained based on solutions to problems from discrete optimization. They allow application of both types of comparisons - binary and multivalent (this fact relates to the tolerance and preference relations. The estimates can be verified in a statistical way; in particular, it is possible to verify the type of the relation. The estimates have been applied by the author to problems regarding forecasting, financial engineering and bio-cybernetics. (original abstract
Nilsson, Håkan; Juslin, Peter; Winman, Anders
2016-01-01
Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014). (c) 2015 APA, all rights reserved).
A residual-based a posteriori error estimator for single-phase Darcy flow in fractured porous media
Chen, Huangxin
2016-12-09
In this paper we develop an a posteriori error estimator for a mixed finite element method for single-phase Darcy flow in a two-dimensional fractured porous media. The discrete fracture model is applied to model the fractures by one-dimensional fractures in a two-dimensional domain. We consider Raviart–Thomas mixed finite element method for the approximation of the coupled Darcy flows in the fractures and the surrounding porous media. We derive a robust residual-based a posteriori error estimator for the problem with non-intersecting fractures. The reliability and efficiency of the a posteriori error estimator are established for the error measured in an energy norm. Numerical results verifying the robustness of the proposed a posteriori error estimator are given. Moreover, our numerical results indicate that the a posteriori error estimator also works well for the problem with intersecting fractures.
Roesler, Elizabeth L.; Grabowski, Timothy B.
2018-01-01
Developing effective monitoring methods for elusive, rare, or patchily distributed species requires extra considerations, such as imperfect detection. Although detection is frequently modeled, the opportunity to assess it empirically is rare, particularly for imperiled species. We used Pecos assiminea (Assiminea pecos), an endangered semiaquatic snail, as a case study to test detection and accuracy issues surrounding quadrat searches. Quadrats (9 × 20 cm; n = 12) were placed in suitable Pecos assiminea habitat and randomly assigned a treatment, defined as the number of empty snail shells (0, 3, 6, or 9). Ten observers rotated through each quadrat, conducting 5-min visual searches for shells. The probability of detecting a shell when present was 67.4 ± 3.0%, but it decreased with the increasing litter depth and fewer number of shells present. The mean (± SE) observer accuracy was 25.5 ± 4.3%. Accuracy was positively correlated to the number of shells in the quadrat and negatively correlated to the number of times a quadrat was searched. The results indicate quadrat surveys likely underrepresent true abundance, but accurately determine the presence or absence. Understanding detection and accuracy of elusive, rare, or imperiled species improves density estimates and aids in monitoring and conservation efforts.