Jump probabilities in the non-Markovian quantum jump method

International Nuclear Information System (INIS)

Haerkoenen, Kari

2010-01-01

The dynamics of a non-Markovian open quantum system described by a general time-local master equation is studied. The propagation of the density operator is constructed in terms of two processes: (i) deterministic evolution and (ii) evolution of a probability density functional in the projective Hilbert space. The analysis provides a derivation for the jump probabilities used in the recently developed non-Markovian quantum jump (NMQJ) method (Piilo et al 2008 Phys. Rev. Lett. 100 180402).

8th International Conference on Soft Methods in Probability and Statistics

CERN Document Server

Giordani, Paolo; Vantaggi, Barbara; Gagolewski, Marek; Gil, María; Grzegorzewski, Przemysław; Hryniewicz, Olgierd

2017-01-01

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.

Information-theoretic methods for estimating of complicated probability distributions

CERN Document Server

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

METHOD OF FOREST FIRES PROBABILITY ASSESSMENT WITH POISSON LAW

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A. S. Plotnikova

2016-01-01

Full Text Available The article describes the method for the forest fire burn probability estimation on a base of Poisson distribution. The λ parameter is assumed to be a mean daily number of fires detected for each Forest Fire Danger Index class within specific period of time. Thus, λ was calculated for spring, summer and autumn seasons separately. Multi-annual daily Forest Fire Danger Index values together with EO-derived hot spot map were input data for the statistical analysis. The major result of the study is generation of the database on forest fire burn probability. Results were validated against EO daily data on forest fires detected over Irkutsk oblast in 2013. Daily weighted average probability was shown to be linked with the daily number of detected forest fires. Meanwhile, there was found a number of fires which were developed when estimated probability was low. The possible explanation of this phenomenon was provided.

The maximum entropy method of moments and Bayesian probability theory

Science.gov (United States)

Bretthorst, G. Larry

2013-08-01

The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.

Constructing inverse probability weights for continuous exposures: a comparison of methods.

Science.gov (United States)

Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S

2014-03-01

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Comments on the sequential probability ratio testing methods

Energy Technology Data Exchange (ETDEWEB)

Racz, A. [Hungarian Academy of Sciences, Budapest (Hungary). Central Research Inst. for Physics

1996-07-01

In this paper the classical sequential probability ratio testing method (SPRT) is reconsidered. Every individual boundary crossing event of the SPRT is regarded as a new piece of evidence about the problem under hypothesis testing. The Bayes method is applied for belief updating, i.e. integrating these individual decisions. The procedure is recommended to use when the user (1) would like to be informed about the tested hypothesis continuously and (2) would like to achieve his final conclusion with high confidence level. (Author).

Molecular machines regulating the release probability of synaptic vesicles at the active zone.

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Christoph eKoerber

2016-03-01

Full Text Available The fusion of synaptic vesicles (SVs with the plasma membrane of the active zone (AZ upon arrival of an action potential (AP at the presynaptic compartment is a tightly regulated probabil-istic process crucial for information transfer. The probability of a SV to release its transmitter content in response to an AP, termed release probability (Pr, is highly diverse both at the level of entire synapses and individual SVs at a given synapse. Differences in Pr exist between different types of synapses, between synapses of the same type, synapses originating from the same axon and even between different SV subpopulations within the same presynaptic terminal. The Pr of SVs at the AZ is set by a complex interplay of different presynaptic properties including the availability of release-ready SVs, the location of the SVs relative to the voltage-gated calcium channels (VGCCs at the AZ, the magnitude of calcium influx upon arrival of the AP, the buffer-ing of calcium ions as well as the identity and sensitivity of the calcium sensor. These properties are not only interconnected, but can also be regulated dynamically to match the requirements of activity patterns mediated by the synapse. Here, we review recent advances in identifying mole-cules and molecular machines taking part in the determination of vesicular Pr at the AZ.

A transmission probability method for calculation of neutron flux distributions in hexagonal geometry

International Nuclear Information System (INIS)

Wasastjerna, F.; Lux, I.

1980-03-01

A transmission probability method implemented in the program TPHEX is described. This program was developed for the calculation of neutron flux distributions in hexagonal light water reactor fuel assemblies. The accuracy appears to be superior to diffusion theory, and the computation time is shorter than that of the collision probability method. (author)

Bayesian maximum posterior probability method for interpreting plutonium urinalysis data

International Nuclear Information System (INIS)

Miller, G.; Inkret, W.C.

1996-01-01

A new internal dosimetry code for interpreting urinalysis data in terms of radionuclide intakes is described for the case of plutonium. The mathematical method is to maximise the Bayesian posterior probability using an entropy function as the prior probability distribution. A software package (MEMSYS) developed for image reconstruction is used. Some advantages of the new code are that it ensures positive calculated dose, it smooths out fluctuating data, and it provides an estimate of the propagated uncertainty in the calculated doses. (author)

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

Science.gov (United States)

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

Estimation of Extreme Response and Failure Probability of Wind Turbines under Normal Operation using Probability Density Evolution Method

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...

A probability-based multi-cycle sorting method for 4D-MRI: A simulation study.

Science.gov (United States)

Liang, Xiao; Yin, Fang-Fang; Liu, Yilin; Cai, Jing

2016-12-01

To develop a novel probability-based sorting method capable of generating multiple breathing cycles of 4D-MRI images and to evaluate performance of this new method by comparing with conventional phase-based methods in terms of image quality and tumor motion measurement. Based on previous findings that breathing motion probability density function (PDF) of a single breathing cycle is dramatically different from true stabilized PDF that resulted from many breathing cycles, it is expected that a probability-based sorting method capable of generating multiple breathing cycles of 4D images may capture breathing variation information missing from conventional single-cycle sorting methods. The overall idea is to identify a few main breathing cycles (and their corresponding weightings) that can best represent the main breathing patterns of the patient and then reconstruct a set of 4D images for each of the identified main breathing cycles. This method is implemented in three steps: (1) The breathing signal is decomposed into individual breathing cycles, characterized by amplitude, and period; (2) individual breathing cycles are grouped based on amplitude and period to determine the main breathing cycles. If a group contains more than 10% of all breathing cycles in a breathing signal, it is determined as a main breathing pattern group and is represented by the average of individual breathing cycles in the group; (3) for each main breathing cycle, a set of 4D images is reconstructed using a result-driven sorting method adapted from our previous study. The probability-based sorting method was first tested on 26 patients' breathing signals to evaluate its feasibility of improving target motion PDF. The new method was subsequently tested for a sequential image acquisition scheme on the 4D digital extended cardiac torso (XCAT) phantom. Performance of the probability-based and conventional sorting methods was evaluated in terms of target volume precision and accuracy as measured

Probability approaching method (PAM) and its application on fuel management optimization

International Nuclear Information System (INIS)

Liu, Z.; Hu, Y.; Shi, G.

2004-01-01

For multi-cycle reloading optimization problem, a new solving scheme is presented. The multi-cycle problem is de-coupled into a number of relatively independent mono-cycle issues, then this non-linear programming problem with complex constraints is solved by an advanced new algorithm -probability approaching method (PAM), which is based on probability theory. The result on simplified core model shows well effect of this new multi-cycle optimization scheme. (authors)

Disadvantage factors for square lattice cells using a collision probability method

International Nuclear Information System (INIS)

Raghav, H.P.

1976-01-01

The flux distribution in an infinite square lattice consisting of cylindrical fuel rods and moderator is calculated by using a collision probability method. Neutrons are assumed to be monoenergetic and the sources as well as scattering are assumed to be isotropic. Carlvik's method for the calculation of collision probability is used. The important features of the method are that the square boundary is treated exactly and the contribution of the surrounding cells is calculated explicitly. The method is programmed in a computer code CELLC. This carries out integration by Simpson's rule. The convergence and accuracy of CELLC is assessed by computing disadvantage factors for the well-known Thie lattices and comparing the results with Monte Carlo and other integral transport theory methods used elsewhere. It is demonstrated that it is not correct to apply the white boundary condition in the Wigner Seitz Cell for low pitch and low cross sections. (orig.) [de

Probability-neighbor method of accelerating geometry treatment in reactor Monte Carlo code RMC

International Nuclear Information System (INIS)

She, Ding; Li, Zeguang; Xu, Qi; Wang, Kan; Yu, Ganglin

2011-01-01

Probability neighbor method (PNM) is proposed in this paper to accelerate geometry treatment of Monte Carlo (MC) simulation and validated in self-developed reactor Monte Carlo code RMC. During MC simulation by either ray-tracking or delta-tracking method, large amounts of time are spent in finding out which cell one particle is located in. The traditional way is to search cells one by one with certain sequence defined previously. However, this procedure becomes very time-consuming when the system contains a large number of cells. Considering that particles have different probability to enter different cells, PNM method optimizes the searching sequence, i.e., the cells with larger probability are searched preferentially. The PNM method is implemented in RMC code and the numerical results show that the considerable time of geometry treatment in MC calculation for complicated systems is saved, especially effective in delta-tracking simulation. (author)

Emission probability determination of {sup 133}Ba by the sum-peak method

Energy Technology Data Exchange (ETDEWEB)

Silva, R.L. da; Almeida, M.C.M. de; Delgado, J.U.; Poledna, R.; Araujo, M.T.F.; Trindade, O.L.; Veras, E.V. de; Santos, A.; Rangel, J.; Ferreira Filho, A.L., E-mail: ronaldo@ird.gov.br, E-mail: marcandida@yahoo.com.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

2016-07-01

The National Laboratory of Metrology Ionizing Radiation (LNMRI/IRD/CNEN) has several measurement methods in order to ensure low uncertainties about the results. Through gamma spectrometry analysis by sum-peak absolute method they were performed the standardization of {sup 133}Ba activity and your emission probability determination of different energies with reduced uncertainties. The advantages of radionuclides calibrations by absolute method are accuracy, low uncertainties and is not necessary the use of radionuclides reference standards. {sup 133}Ba is used in research laboratories on calibration detectors in different work areas. The uncertainties for the activity and for the emission probability results are lower than 1%. (author)

DEVELOPMENT OF THE PROBABLY-GEOGRAPHICAL FORECAST METHOD FOR DANGEROUS WEATHER PHENOMENA

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Elena S. Popova

2015-12-01

Full Text Available This paper presents a scheme method of probably-geographical forecast for dangerous weather phenomena. Discuss two general realization stages of this method. Emphasize that developing method is response to actual questions of modern weather forecast and it’s appropriate phenomena: forecast is carried out for specific point in space and appropriate moment of time.

An Adjusted Probability Method for the Identification of Sociometric Status in Classrooms

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Francisco J. García Bacete

2017-10-01

Full Text Available Objective: The aim of this study was to test the performance of an adjusted probability method for sociometric classification proposed by García Bacete (GB in comparison with two previous methods. Specific goals were to examine the overall agreement between methods, the behavioral correlates of each sociometric group, the sources for discrepant classifications between methods, the behavioral profiles of discrepant and consistent cases between methods, and age differences.Method: We compared the GB adjusted probability method with the standard score model proposed by Coie and Dodge (CD and the probability score model proposed by Newcomb and Bukowski (NB. The GB method is an adaptation of the NB method, cutoff scores are derived from the distribution of raw liked most and liked least scores in each classroom instead of using fixed and absolute scores as does NB method. The criteria for neglected status are also modified by the GB method. Participants were 569 children (45% girls from 23 elementary school classrooms (13 Grades 1–2, 10 Grades 5–6.Results: We found agreement as well as differences between the three methods. The CD method yielded discrepancies in the classifications because of its dependence on z-scores and composite dimensions. The NB method was less optimal in the validation of the behavioral characteristics of the sociometric groups, because of its fixed cutoffs for identifying preferred, rejected, and controversial children, and not differentiating between positive and negative nominations for neglected children. The GB method addressed some of the limitations of the other two methods. It improved the classified of neglected students, as well as discrepant cases of the preferred, rejected, and controversial groups. Agreement between methods was higher with the oldest children.Conclusion: GB is a valid sociometric method as evidences by the behavior profiles of the sociometric status groups identified with this method.

Reliability analysis of reactor systems by applying probability method; Analiza pouzdanosti reaktorskih sistema primenom metoda verovatnoce

Energy Technology Data Exchange (ETDEWEB)

Milivojevic, S [Institute of Nuclear Sciences Boris Kidric, Vinca, Beograd (Serbia and Montenegro)

1974-12-15

Probability method was chosen for analysing the reactor system reliability is considered realistic since it is based on verified experimental data. In fact this is a statistical method. The probability method developed takes into account the probability distribution of permitted levels of relevant parameters and their particular influence on the reliability of the system as a whole. The proposed method is rather general, and was used for problem of thermal safety analysis of reactor system. This analysis enables to analyze basic properties of the system under different operation conditions, expressed in form of probability they show the reliability of the system on the whole as well as reliability of each component.

Probability evolution method for exit location distribution

Science.gov (United States)

Zhu, Jinjie; Chen, Zhen; Liu, Xianbin

2018-03-01

The exit problem in the framework of the large deviation theory has been a hot topic in the past few decades. The most probable escape path in the weak-noise limit has been clarified by the Freidlin-Wentzell action functional. However, noise in real physical systems cannot be arbitrarily small while noise with finite strength may induce nontrivial phenomena, such as noise-induced shift and noise-induced saddle-point avoidance. Traditional Monte Carlo simulation of noise-induced escape will take exponentially large time as noise approaches zero. The majority of the time is wasted on the uninteresting wandering around the attractors. In this paper, a new method is proposed to decrease the escape simulation time by an exponentially large factor by introducing a series of interfaces and by applying the reinjection on them. This method can be used to calculate the exit location distribution. It is verified by examining two classical examples and is compared with theoretical predictions. The results show that the method performs well for weak noise while may induce certain deviations for large noise. Finally, some possible ways to improve our method are discussed.

An adjusted probability method for the identification of sociometric status in classrooms

NARCIS (Netherlands)

García Bacete, F.J.; Cillessen, A.H.N.

2017-01-01

Objective: The aim of this study was to test the performance of an adjusted probability method for sociometric classification proposed by García Bacete (GB) in comparison with two previous methods. Specific goals were to examine the overall agreement between methods, the behavioral correlates of

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

Science.gov (United States)

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.

Approximations to the Probability of Failure in Random Vibration by Integral Equation Methods

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

Close approximations to the first passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first passage probability density function and the distribution function for the time interval spent below a barrier before...... passage probability density. The results of the theory agree well with simulation results for narrow banded processes dominated by a single frequency, as well as for bimodal processes with 2 dominating frequencies in the structural response....... outcrossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval, and hence for the first...

Numerical Simulation of Tubular Pumping Systems with Different Regulation Methods

Science.gov (United States)

Zhu, Honggeng; Zhang, Rentian; Deng, Dongsheng; Feng, Xusong; Yao, Linbi

2010-06-01

Since the flow in tubular pumping systems is basically along axial direction and passes symmetrically through the impeller, most satisfying the basic hypotheses in the design of impeller and having higher pumping system efficiency in comparison with vertical pumping system, they are being widely applied to low-head pumping engineering. In a pumping station, the fluctuation of water levels in the sump and discharge pool is most common and at most time the pumping system runs under off-design conditions. Hence, the operation of pump has to be flexibly regulated to meet the needs of flow rates, and the selection of regulation method is as important as that of pump to reduce operation cost and achieve economic operation. In this paper, the three dimensional time-averaged Navier-Stokes equations are closed by RNG κ-ɛ turbulent model, and two tubular pumping systems with different regulation methods, equipped with the same pump model but with different designed system structures, are numerically simulated respectively to predict the pumping system performances and analyze the influence of regulation device and help designers make final decision in the selection of design schemes. The computed results indicate that the pumping system with blade-adjusting device needs longer suction box, and the increased hydraulic loss will lower the pumping system efficiency in the order of 1.5%. The pumping system with permanent magnet motor, by means of variable speed regulation, obtains higher system efficiency partly for shorter suction box and partly for different structure design. Nowadays, the varied speed regulation is realized by varied frequency device, the energy consumption of which is about 3˜4% of output power of the motor. Hence, when the efficiency of variable frequency device is considered, the total pumping system efficiency will probably be lower.

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

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)

A method for the calculation of the cumulative failure probability distribution of complex repairable systems

International Nuclear Information System (INIS)

Caldarola, L.

1976-01-01

A method is proposed for the analytical evaluation of the cumulative failure probability distribution of complex repairable systems. The method is based on a set of integral equations each one referring to a specific minimal cut set of the system. Each integral equation links the unavailability of a minimal cut set to its failure probability density distribution and to the probability that the minimal cut set is down at the time t under the condition that it was down at time t'(t'<=t). The limitations for the applicability of the method are also discussed. It has been concluded that the method is applicable if the process describing the failure of a minimal cut set is a 'delayed semi-regenerative process'. (Auth.)

Calculation of parameter failure probability of thermodynamic system by response surface and importance sampling method

International Nuclear Information System (INIS)

Shang Yanlong; Cai Qi; Chen Lisheng; Zhang Yangwei

2012-01-01

In this paper, the combined method of response surface and importance sampling was applied for calculation of parameter failure probability of the thermodynamic system. The mathematics model was present for the parameter failure of physics process in the thermodynamic system, by which the combination arithmetic model of response surface and importance sampling was established, then the performance degradation model of the components and the simulation process of parameter failure in the physics process of thermodynamic system were also present. The parameter failure probability of the purification water system in nuclear reactor was obtained by the combination method. The results show that the combination method is an effective method for the calculation of the parameter failure probability of the thermodynamic system with high dimensionality and non-linear characteristics, because of the satisfactory precision with less computing time than the direct sampling method and the drawbacks of response surface method. (authors)

COVAL, Compound Probability Distribution for Function of Probability Distribution

International Nuclear Information System (INIS)

Astolfi, M.; Elbaz, J.

1979-01-01

1 - Nature of the physical problem solved: Computation of the probability distribution of a function of variables, given the probability distribution of the variables themselves. 'COVAL' has been applied to reliability analysis of a structure subject to random loads. 2 - Method of solution: Numerical transformation of probability distributions

Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used

Directory of Open Access Journals (Sweden)

Cinicioglu Esma Nur

2014-01-01

Full Text Available Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of a decision theory of belief functions gives rise to the need to use the probability transformation methods for decision making. For representation of statistical evidence, the class of consonant belief functions is used which is not closed under Dempster’s rule of combination but is closed under Walley’s rule of combination. In this research, it is shown that the outcomes obtained using both Dempster’s and Walley’s rules do result in different probability distributions when pignistic transformation is used. However, when plausibility transformation is used, they do result in the same probability distribution. This result shows that the choice of the combination rule and probability transformation method may have a significant effect on decision making since it may change the choice of the decision alternative selected. This result is illustrated via an example of missile type identification.

Dynamic probability evaluation of safety levels of earth-rockfill dams using Bayesian approach

Directory of Open Access Journals (Sweden)

Zi-wu Fan

2009-06-01

Full Text Available In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined with the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

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

Unification of field theory and maximum entropy methods for learning probability densities

OpenAIRE

Kinney, Justin B.

2014-01-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy de...

A Comparison of Sequential and GPU Implementations of Iterative Methods to Compute Reachability Probabilities

Directory of Open Access Journals (Sweden)

Elise Cormie-Bowins

2012-10-01

Full Text Available We consider the problem of computing reachability probabilities: given a Markov chain, an initial state of the Markov chain, and a set of goal states of the Markov chain, what is the probability of reaching any of the goal states from the initial state? This problem can be reduced to solving a linear equation Ax = b for x, where A is a matrix and b is a vector. We consider two iterative methods to solve the linear equation: the Jacobi method and the biconjugate gradient stabilized (BiCGStab method. For both methods, a sequential and a parallel version have been implemented. The parallel versions have been implemented on the compute unified device architecture (CUDA so that they can be run on a NVIDIA graphics processing unit (GPU. From our experiments we conclude that as the size of the matrix increases, the CUDA implementations outperform the sequential implementations. Furthermore, the BiCGStab method performs better than the Jacobi method for dense matrices, whereas the Jacobi method does better for sparse ones. Since the reachability probabilities problem plays a key role in probabilistic model checking, we also compared the implementations for matrices obtained from a probabilistic model checker. Our experiments support the conjecture by Bosnacki et al. that the Jacobi method is superior to Krylov subspace methods, a class to which the BiCGStab method belongs, for probabilistic model checking.

A New Self-Constrained Inversion Method of Potential Fields Based on Probability Tomography

Science.gov (United States)

Sun, S.; Chen, C.; WANG, H.; Wang, Q.

2014-12-01

The self-constrained inversion method of potential fields uses a priori information self-extracted from potential field data. Differing from external a priori information, the self-extracted information are generally parameters derived exclusively from the analysis of the gravity and magnetic data (Paoletti et al., 2013). Here we develop a new self-constrained inversion method based on probability tomography. Probability tomography doesn't need any priori information, as well as large inversion matrix operations. Moreover, its result can describe the sources, especially the distribution of which is complex and irregular, entirely and clearly. Therefore, we attempt to use the a priori information extracted from the probability tomography results to constrain the inversion for physical properties. The magnetic anomaly data was taken as an example in this work. The probability tomography result of magnetic total field anomaly(ΔΤ) shows a smoother distribution than the anomalous source and cannot display the source edges exactly. However, the gradients of ΔΤ are with higher resolution than ΔΤ in their own direction, and this characteristic is also presented in their probability tomography results. So we use some rules to combine the probability tomography results of ∂ΔΤ⁄∂x, ∂ΔΤ⁄∂y and ∂ΔΤ⁄∂z into a new result which is used for extracting a priori information, and then incorporate the information into the model objective function as spatial weighting functions to invert the final magnetic susceptibility. Some magnetic synthetic examples incorporated with and without a priori information extracted from the probability tomography results were made to do comparison, results of which show that the former are more concentrated and with higher resolution of the source body edges. This method is finally applied in an iron mine in China with field measured ΔΤ data and performs well. ReferencesPaoletti, V., Ialongo, S., Florio, G., Fedi, M

The application of probability methods for safeguards purposes

International Nuclear Information System (INIS)

Rumyantsev, A.N.

1976-01-01

The authors consider possible ways of applying probability methods to solve problems involved in accounting for nuclear materials. The increase in the flow of nuclear materials subject to IAEA safeguards makes it necessary to increase the accuracy of determination of the actual quantities of nuclear materials at all stages of their processing and use. It is proposed that the IAEA's automated system of accounting for nuclear materials, based on accounting information for each material balance zone and the results of random experimental checks performed by IAEA inspectors, be supplemented with mathematical models of the flow of nuclear materials in each balance zone based on the data supplied for each facility in the balance zone when it was placed under safeguards. The statistical error in determining the material balance and the material unaccounted for can be considerably reduced in this way even if the experimental control methods are retained. (author)

The exact probability distribution of the rank product statistics for replicated experiments.

Science.gov (United States)

Eisinga, Rob; Breitling, Rainer; Heskes, Tom

2013-03-18

The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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

Discrete probability models and methods probability on graphs and trees, Markov chains and random fields, entropy and coding

CERN Document Server

Brémaud, Pierre

2017-01-01

The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book. .

Multiregion, multigroup collision probability method with white boundary condition for light water reactor thermalization calculations

International Nuclear Information System (INIS)

Ozgener, B.; Ozgener, H.A.

2005-01-01

A multiregion, multigroup collision probability method with white boundary condition is developed for thermalization calculations of light water moderated reactors. Hydrogen scatterings are treated by Nelkin's kernel while scatterings from other nuclei are assumed to obey the free-gas scattering kernel. The isotropic return (white) boundary condition is applied directly by using the appropriate collision probabilities. Comparisons with alternate numerical methods show the validity of the present formulation. Comparisons with some experimental results indicate that the present formulation is capable of calculating disadvantage factors which are closer to the experimental results than alternative methods

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

Using the probability method for multigroup calculations of reactor cells in a thermal energy range

International Nuclear Information System (INIS)

Rubin, I.E.; Pustoshilova, V.S.

1984-01-01

The possibility of using the transmission probability method with performance inerpolation for determining spatial-energy neutron flux distribution in cells of thermal heterogeneous reactors is considered. The results of multigroup calculations of several uranium-water plane and cylindrical cells with different fuel enrichment in a thermal energy range are given. A high accuracy of results is obtained with low computer time consumption. The use of the transmission probability method is particularly reasonable in algorithms of the programmes compiled computer with significant reserve of internal memory

The Most Probable Limit of Detection (MPL) for rapid microbiological methods

NARCIS (Netherlands)

Verdonk, G.P.H.T.; Willemse, M.J.; Hoefs, S.G.G.; Cremers, G.; Heuvel, E.R. van den

Classical microbiological methods have nowadays unacceptably long cycle times. Rapid methods, available on the market for decades, are already applied within the clinical and food industry, but the implementation in pharmaceutical industry is hampered by for instance stringent regulations on

The most probable limit of detection (MPL) for rapid microbiological methods

NARCIS (Netherlands)

Verdonk, G.P.H.T.; Willemse, M.J.; Hoefs, S.G.G.; Cremers, G.; Heuvel, van den E.R.

2010-01-01

Classical microbiological methods have nowadays unacceptably long cycle times. Rapid methods, available on the market for decades, are already applied within the clinical and food industry, but the implementation in pharmaceutical industry is hampered by for instance stringent regulations on

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

Science.gov (United States)

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.

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

CERN Document Server

Dannheim, Dominik; Voigt, Alexander; Grahn, Karl-Johan; Speckmayer, Peter

2009-01-01

Probability-Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. To efficiently use large event samples to estimate the probability density, a binary search tree (range searching) is used in the PDE-RS implementation. It is a generalisation of standard likelihood methods and a powerful classification tool for problems with highly non-linearly correlated observables. In this paper, we present an innovative improvement of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multidimensional phase space, minimizing the variance of the signal and background densities inside the cells. The binned density information is stored in binary trees, allowing for a very ...

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)

Improved collision probability method for thermal-neutron-flux calculation in a cylindrical reactor cell

International Nuclear Information System (INIS)

Bosevski, T.

1986-01-01

An improved collision probability method for thermal-neutron-flux calculation in a cylindrical reactor cell has been developed. Expanding the neutron flux and source into a series of even powers of the radius, one' gets a convenient method for integration of the one-energy group integral transport equation. It is shown that it is possible to perform an analytical integration in the x-y plane in one variable and to use the effective Gaussian integration over another one. Choosing a convenient distribution of space points in fuel and moderator the transport matrix calculation and cell reaction rate integration were condensed. On the basis of the proposed method, the computer program DISKRET for the ZUSE-Z 23 K computer has been written. The suitability of the proposed method for the calculation of the thermal-neutron-flux distribution in a reactor cell can be seen from the test results obtained. Compared with the other collision probability methods, the proposed treatment excels with a mathematical simplicity and a faster convergence. (author)

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

Science.gov (United States)

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

The probability estimate of the defects of the asynchronous motors based on the complex method of diagnostics

Science.gov (United States)

Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

2017-10-01

This article is devoted to the development of a method for probability estimate of failure of an asynchronous motor as a part of electric drive with a frequency converter. The proposed method is based on a comprehensive method of diagnostics of vibration and electrical characteristics that take into account the quality of the supply network and the operating conditions. The developed diagnostic system allows to increase the accuracy and quality of diagnoses by determining the probability of failure-free operation of the electromechanical equipment, when the parameters deviate from the norm. This system uses an artificial neural networks (ANNs). The results of the system for estimator the technical condition are probability diagrams of the technical state and quantitative evaluation of the defects of the asynchronous motor and its components.

Collision probability in two-dimensional lattice by ray-trace method and its applications to cell calculations

International Nuclear Information System (INIS)

Tsuchihashi, Keichiro

1985-03-01

A series of formulations to evaluate collision probability for multi-region cells expressed by either of three one-dimensional coordinate systems (plane, sphere and cylinder) or by the general two-dimensional cylindrical coordinate system is presented. They are expressed in a suitable form to have a common numerical process named ''Ray-Trace'' method. Applications of the collision probability method to two optional treatments for the resonance absorption are presented. One is a modified table-look-up method based on the intermediate resonance approximation, and the other is a rigorous method to calculate the resonance absorption in a multi-region cell in which nearly continuous energy spectra of the resonance neutron range can be solved and interaction effect between different resonance nuclides can be evaluated. Two works on resonance absorption in a doubly heterogeneous system with grain structure are presented. First, the effect of a random distribution of particles embedded in graphite diluent on the resonance integral is studied. Next, the ''Accretion'' method proposed by Leslie and Jonsson to define the collision probability in a doubly heterogeneous system is applied to evaluate the resonance absorption in coated particles dispersed in fuel pellet of the HTGR. Several optional models are proposed to define the collision rates in the medium with the microscopic heterogeneity. By making use of the collision probability method developed by the present study, the JAERI thermal reactor standard nuclear design code system SRAC has been developed. Results of several benchmark tests for the SRAC are presented. The analyses of critical experiments of the SHE, DCA, and FNR show good agreement of critical masses with their experimental values. (J.P.N.)

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.

Optimal methods for fitting probability distributions to propagule retention time in studies of zoochorous dispersal.

Science.gov (United States)

Viana, Duarte S; Santamaría, Luis; Figuerola, Jordi

2016-02-01

Propagule retention time is a key factor in determining propagule dispersal distance and the shape of "seed shadows". Propagules dispersed by animal vectors are either ingested and retained in the gut until defecation or attached externally to the body until detachment. Retention time is a continuous variable, but it is commonly measured at discrete time points, according to pre-established sampling time-intervals. Although parametric continuous distributions have been widely fitted to these interval-censored data, the performance of different fitting methods has not been evaluated. To investigate the performance of five different fitting methods, we fitted parametric probability distributions to typical discretized retention-time data with known distribution using as data-points either the lower, mid or upper bounds of sampling intervals, as well as the cumulative distribution of observed values (using either maximum likelihood or non-linear least squares for parameter estimation); then compared the estimated and original distributions to assess the accuracy of each method. We also assessed the robustness of these methods to variations in the sampling procedure (sample size and length of sampling time-intervals). Fittings to the cumulative distribution performed better for all types of parametric distributions (lognormal, gamma and Weibull distributions) and were more robust to variations in sample size and sampling time-intervals. These estimated distributions had negligible deviations of up to 0.045 in cumulative probability of retention times (according to the Kolmogorov-Smirnov statistic) in relation to original distributions from which propagule retention time was simulated, supporting the overall accuracy of this fitting method. In contrast, fitting the sampling-interval bounds resulted in greater deviations that ranged from 0.058 to 0.273 in cumulative probability of retention times, which may introduce considerable biases in parameter estimates. We

Probability Density Function Method for Observing Reconstructed Attractor Structure

Institute of Scientific and Technical Information of China (English)

陆宏伟; 陈亚珠; 卫青

2004-01-01

Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men. PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor. To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure. Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6 - 6.5 dimensional complex dynamical systems. It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough. A cluster effect mechanism is presented to explain this phenomenon. By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated. Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.

A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models

International Nuclear Information System (INIS)

Echard, B.; Gayton, N.; Lemaire, M.; Relun, N.

2013-01-01

Applying reliability methods to a complex structure is often delicate for two main reasons. First, such a structure is fortunately designed with codified rules leading to a large safety margin which means that failure is a small probability event. Such a probability level is difficult to assess efficiently. Second, the structure mechanical behaviour is modelled numerically in an attempt to reproduce the real response and numerical model tends to be more and more time-demanding as its complexity is increased to improve accuracy and to consider particular mechanical behaviour. As a consequence, performing a large number of model computations cannot be considered in order to assess the failure probability. To overcome these issues, this paper proposes an original and easily implementable method called AK-IS for active learning and Kriging-based Importance Sampling. This new method is based on the AK-MCS algorithm previously published by Echard et al. [AK-MCS: an active learning reliability method combining Kriging and Monte Carlo simulation. Structural Safety 2011;33(2):145–54]. It associates the Kriging metamodel and its advantageous stochastic property with the Importance Sampling method to assess small failure probabilities. It enables the correction or validation of the FORM approximation with only a very few mechanical model computations. The efficiency of the method is, first, proved on two academic applications. It is then conducted for assessing the reliability of a challenging aerospace case study submitted to fatigue.

Methods for estimating drought streamflow probabilities for Virginia streams

Science.gov (United States)

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.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models

NARCIS (Netherlands)

Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.

2012-01-01

PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator

Is probability of frequency too narrow?

International Nuclear Information System (INIS)

Martz, H.F.

1993-01-01

Modern methods of statistical data analysis, such as empirical and hierarchical Bayesian methods, should find increasing use in future Probabilistic Risk Assessment (PRA) applications. In addition, there will be a more formalized use of expert judgment in future PRAs. These methods require an extension of the probabilistic framework of PRA, in particular, the popular notion of probability of frequency, to consideration of frequency of frequency, frequency of probability, and probability of probability. The genesis, interpretation, and examples of these three extended notions are discussed

Estimation method for first excursion probability of secondary system with impact and friction using maximum response

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)

Comparing a recursive digital filter with the moving-average and sequential probability-ratio detection methods for SNM portal monitors

International Nuclear Information System (INIS)

Fehlau, P.E.

1993-01-01

The author compared a recursive digital filter proposed as a detection method for French special nuclear material monitors with the author's detection methods, which employ a moving-average scaler or a sequential probability-ratio test. Each of these nine test subjects repeatedly carried a test source through a walk-through portal monitor that had the same nuisance-alarm rate with each method. He found that the average detection probability for the test source is also the same for each method. However, the recursive digital filter may have on drawback: its exponentially decreasing response to past radiation intensity prolongs the impact of any interference from radiation sources of radiation-producing machinery. He also examined the influence of each test subject on the monitor's operation by measuring individual attenuation factors for background and source radiation, then ranked the subjects' attenuation factors against their individual probabilities for detecting the test source. The one inconsistent ranking was probably caused by that subject's unusually long stride when passing through the portal

An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems

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

Assessment procedure and probability determination methods of aircraft crash events in siting for nuclear power plants

International Nuclear Information System (INIS)

Zheng Qiyan; Zhang Lijun; Huang Weiqi; Yin Qingliao

2010-01-01

Assessment procedure of aircraft crash events in siting for nuclear power plants, and the methods of probability determination in two different stages of prelimi- nary screening and detailed evaluation are introduced in this paper. Except for general air traffic, airport operations and aircraft in the corridor, the probability of aircraft crash by military operation in the military airspaces is considered here. (authors)

Sensitivity of the probability of failure to probability of detection curve regions

International Nuclear Information System (INIS)

Garza, J.; Millwater, H.

2016-01-01

Non-destructive inspection (NDI) techniques have been shown to play a vital role in fracture control plans, structural health monitoring, and ensuring availability and reliability of piping, pressure vessels, mechanical and aerospace equipment. Probabilistic fatigue simulations are often used in order to determine the efficacy of an inspection procedure with the NDI method modeled as a probability of detection (POD) curve. These simulations can be used to determine the most advantageous NDI method for a given application. As an aid to this process, a first order sensitivity method of the probability-of-failure (POF) with respect to regions of the POD curve (lower tail, middle region, right tail) is developed and presented here. The sensitivity method computes the partial derivative of the POF with respect to a change in each region of a POD or multiple POD curves. The sensitivities are computed at no cost by reusing the samples from an existing Monte Carlo (MC) analysis. A numerical example is presented considering single and multiple inspections. - Highlights: • Sensitivities of probability-of-failure to a region of probability-of-detection curve. • The sensitivities are computed with negligible cost. • Sensitivities identify the important region of a POD curve. • Sensitivities can be used as a guide to selecting the optimal POD curve.

The application of probability methods with a view to improving the quality of equipment

International Nuclear Information System (INIS)

Carnino, A.; Gachot, B.; Greppo, J.-F.; Guitton, J.

1976-01-01

After stating that reliability and availability could be considered as parameters allowing the quality of equipment to be estimated, the chief aspects of the use of probability methods in the field of quality is described. These methods are mainly applied at the design, operation and maintenance level of the equipment, as well as at the compilation stage of the corresponding data [fr

Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

Science.gov (United States)

Wehling, Paul; LaBudde, Robert A; Brunelle, Sharon L; Nelson, Maria T

2011-01-01

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.

A probability space for quantum models

Science.gov (United States)

Lemmens, L. F.

2017-06-01

A probability space contains a set of outcomes, a collection of events formed by subsets of the set of outcomes and probabilities defined for all events. A reformulation in terms of propositions allows to use the maximum entropy method to assign the probabilities taking some constraints into account. The construction of a probability space for quantum models is determined by the choice of propositions, choosing the constraints and making the probability assignment by the maximum entropy method. This approach shows, how typical quantum distributions such as Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein are partly related with well-known classical distributions. The relation between the conditional probability density, given some averages as constraints and the appropriate ensemble is elucidated.

Qualification of the calculational methods of the fluence in the pressurised water reactors. Improvement of the cross sections treatment by the probability table method

International Nuclear Information System (INIS)

Zheng, S.H.

1994-01-01

It is indispensable to know the fluence on the nuclear reactor pressure vessel. The cross sections and their treatment have an important rule to this problem. In this study, two ''benchmarks'' have been interpreted by the Monte Carlo transport program TRIPOLI to qualify the calculational method and the cross sections used in the calculations. For the treatment of the cross sections, the multigroup method is usually used but it exists some problems such as the difficulty to choose the weighting function and the necessity of a great number of energy to represent well the cross section's fluctuation. In this thesis, we propose a new method called ''Probability Table Method'' to treat the neutron cross sections. For the qualification, a program of the simulation of neutron transport by the Monte Carlo method in one dimension has been written; the comparison of multigroup's results and probability table's results shows the advantages of this new method. The probability table has also been introduced in the TRIPOLI program; the calculational results of the iron deep penetration benchmark has been improved by comparing with the experimental results. So it is interest to use this new method in the shielding and neutronic calculation. (author). 42 refs., 109 figs., 36 tabs

Response and reliability analysis of nonlinear uncertain dynamical structures by the probability density evolution method

DEFF Research Database (Denmark)

Nielsen, Søren R. K.; Peng, Yongbo; Sichani, Mahdi Teimouri

2016-01-01

The paper deals with the response and reliability analysis of hysteretic or geometric nonlinear uncertain dynamical systems of arbitrary dimensionality driven by stochastic processes. The approach is based on the probability density evolution method proposed by Li and Chen (Stochastic dynamics...... of structures, 1st edn. Wiley, London, 2009; Probab Eng Mech 20(1):33–44, 2005), which circumvents the dimensional curse of traditional methods for the determination of non-stationary probability densities based on Markov process assumptions and the numerical solution of the related Fokker–Planck and Kolmogorov......–Feller equations. The main obstacle of the method is that a multi-dimensional convolution integral needs to be carried out over the sample space of a set of basic random variables, for which reason the number of these need to be relatively low. In order to handle this problem an approach is suggested, which...

Analytic methods in applied probability in memory of Fridrikh Karpelevich

CERN Document Server

Suhov, Yu M

2002-01-01

This volume is dedicated to F. I. Karpelevich, an outstanding Russian mathematician who made important contributions to applied probability theory. The book contains original papers focusing on several areas of applied probability and its uses in modern industrial processes, telecommunications, computing, mathematical economics, and finance. It opens with a review of Karpelevich's contributions to applied probability theory and includes a bibliography of his works. Other articles discuss queueing network theory, in particular, in heavy traffic approximation (fluid models). The book is suitable

Collision probability method for discrete presentation of space in cylindrical cell

International Nuclear Information System (INIS)

Bosevski, T.

1969-08-01

A suitable numerical method for integration of one-group integral transport equation is obtained by series expansion of flux and neutron source by radius squared, when calculating the parameters of cylindrically symmetric reactor cell. Separation of variables in (x,y) plane enables analytical integration in one direction and efficient Gauss quadrature formula in the second direction. White boundary condition is used for determining the neutron balance. Suitable choice of spatial points distribution in the fuel and moderator condenses the procedure for determining the transport matrix and accelerates the convergence when calculating the absorption in the reactor cell. In comparison to other collision probability methods the proposed procedure is a simple mathematical model which demands smaller computer capacity and shorter computing time

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2013-01-01

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications. The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended...

Probability of satellite collision

Science.gov (United States)

Mccarter, J. W.

1972-01-01

A method is presented for computing the probability of a collision between a particular artificial earth satellite and any one of the total population of earth satellites. The collision hazard incurred by the proposed modular Space Station is assessed using the technique presented. The results of a parametric study to determine what type of satellite orbits produce the greatest contribution to the total collision probability are presented. Collision probability for the Space Station is given as a function of Space Station altitude and inclination. Collision probability was also parameterized over miss distance and mission duration.

Neutron transport by collision probability method in complicated geometries

International Nuclear Information System (INIS)

Constantin, Marin

2000-01-01

For the first flight collision probability (FFCP) method a rapidly increasing of the memory requirements and execution time with the number of discrete regions occurs. Generally, the use of the method is restricted at cell/supercell level. However, the amazing developments both in computer hardware and computer architecture allow a real extending of the problems' domain and a more detailed treatment of the geometry. Two ways are discussed into the paper: the direct design of new codes and the improving of the mainframe old versions. The author's experience is focused on the performances' improving of the 3D integral transport code PIJXYZ (from an old version to a modern one) and on the design and developing of the 2D transport code CP 2 D in the last years. In the first case an optimization process have been performed before the parallelization. In the second a modular design and the newest techniques (factorization of the geometry, the macrobands method, the mobile set of chords, the automatic calculation of the integration error, optimal algorithms for the innermost programming level, the mixed method for tracking process and CPs calculation, etc.) were adopted. In both cases the parallelization uses a PCs network system. Some short examples for CP 2 D and PIJXYZ calculation are presented: reactivity void effect in typical CANDU cells using a multistratified coolant model, a problem of some adjacent fuel assemblies, CANDU reactivity devices 3D simulation. (author)

Choice Probability Generating Functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel L; Bierlaire, Michel

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications....

Theory and analysis of accuracy for the method of characteristics direction probabilities with boundary averaging

International Nuclear Information System (INIS)

Liu, Zhouyu; Collins, Benjamin; Kochunas, Brendan; Downar, Thomas; Xu, Yunlin; Wu, Hongchun

2015-01-01

Highlights: • The CDP combines the benefits of the CPM’s efficiency and the MOC’s flexibility. • Boundary averaging reduces the computation effort with losing minor accuracy. • An analysis model is used to justify the choice of optimize averaging strategy. • Numerical results show the performance and accuracy. - Abstract: The method of characteristic direction probabilities (CDP) combines the benefits of the collision probability method (CPM) and the method of characteristics (MOC) for the solution of the integral form of the Botlzmann Transport Equation. By coupling only the fine regions traversed by the characteristic rays in a particular direction, the computational effort required to calculate the probability matrices and to solve the matrix system is considerably reduced compared to the CPM. Furthermore, boundary averaging is performed to reduce the storage and computation but the capability of dealing with complicated geometries is preserved since the same ray tracing information is used as in MOC. An analysis model for the outgoing angular flux is used to analyze a variety of outgoing angular flux averaging methods for the boundary and to justify the choice of optimize averaging strategy. The boundary average CDP method was then implemented in the Michigan PArallel Characteristic based Transport (MPACT) code to perform 2-D and 3-D transport calculations. The numerical results are given for different cases to show the effect of averaging on the outgoing angular flux, region scalar flux and the eigenvalue. Comparison of the results with the case with no averaging demonstrates that an angular dependent averaging strategy is possible for the CDP to improve its computational performance without compromising the achievable accuracy

α-Cut method based importance measure for criticality analysis in fuzzy probability – Based fault tree analysis

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Widodo, Surip; Tjahjono, Hendro

2017-01-01

Highlights: •FPFTA deals with epistemic uncertainty using fuzzy probability. •Criticality analysis is important for reliability improvement. •An α-cut method based importance measure is proposed for criticality analysis in FPFTA. •The α-cut method based importance measure utilises α-cut multiplication, α-cut subtraction, and area defuzzification technique. •Benchmarking confirm that the proposed method is feasible for criticality analysis in FPFTA. -- Abstract: Fuzzy probability – based fault tree analysis (FPFTA) has been recently developed and proposed to deal with the limitations of conventional fault tree analysis. In FPFTA, reliabilities of basic events, intermediate events and top event are characterized by fuzzy probabilities. Furthermore, the quantification of the FPFTA is based on fuzzy multiplication rule and fuzzy complementation rule to propagate uncertainties from basic event to the top event. Since the objective of the fault tree analysis is to improve the reliability of the system being evaluated, it is necessary to find the weakest path in the system. For this purpose, criticality analysis can be implemented. Various importance measures, which are based on conventional probabilities, have been developed and proposed for criticality analysis in fault tree analysis. However, not one of those importance measures can be applied for criticality analysis in FPFTA, which is based on fuzzy probability. To be fully applied in nuclear power plant probabilistic safety assessment, FPFTA needs to have its corresponding importance measure. The objective of this study is to develop an α-cut method based importance measure to evaluate and rank the importance of basic events for criticality analysis in FPFTA. To demonstrate the applicability of the proposed measure, a case study is performed and its results are then benchmarked to the results generated by the four well known importance measures in conventional fault tree analysis. The results

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

Science.gov (United States)

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

A probability evaluation method of early deterioration condition for the critical components of wind turbine generator systems

DEFF Research Database (Denmark)

Hu, Y.; Li, H.; Liao, X

2016-01-01

method of early deterioration condition for critical components based only on temperature characteristic parameters. First, the dynamic threshold of deterioration degree function was proposed by analyzing the operational data between temperature and rotor speed. Second, a probability evaluation method...... of early deterioration condition was presented. Finally, two cases showed the validity of the proposed probability evaluation method in detecting early deterioration condition and in tracking their further deterioration for the critical components.......This study determines the early deterioration condition of critical components for a wind turbine generator system (WTGS). Due to the uncertainty nature of the fluctuation and intermittence of wind, early deterioration condition evaluation poses a challenge to the traditional vibration...

Concise method for evaluating the probability distribution of the marginal cost of power generation

International Nuclear Information System (INIS)

Zhang, S.H.; Li, Y.Z.

2000-01-01

In the developing electricity market, many questions on electricity pricing and the risk modelling of forward contracts require the evaluation of the expected value and probability distribution of the short-run marginal cost of power generation at any given time. A concise forecasting method is provided, which is consistent with the definitions of marginal costs and the techniques of probabilistic production costing. The method embodies clear physical concepts, so that it can be easily understood theoretically and computationally realised. A numerical example has been used to test the proposed method. (author)

A prototype method for diagnosing high ice water content probability using satellite imager data

Science.gov (United States)

Yost, Christopher R.; Bedka, Kristopher M.; Minnis, Patrick; Nguyen, Louis; Strapp, J. Walter; Palikonda, Rabindra; Khlopenkov, Konstantin; Spangenberg, Douglas; Smith, William L., Jr.; Protat, Alain; Delanoe, Julien

2018-03-01

Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

LAMP-B: a Fortran program set for the lattice cell analysis by collision probability method

International Nuclear Information System (INIS)

Tsuchihashi, Keiichiro

1979-02-01

Nature of physical problem solved: LAMB-B solves an integral transport equation by the collision probability method for many variety of lattice cell geometries: spherical, plane and cylindrical lattice cell; square and hexagonal arrays of pin rods; annular clusters and square clusters. LAMP-B produces homogenized constants for multi and/or few group diffusion theory programs. Method of solution: LAMP-B performs an exact numerical integration to obtain the collision probabilities. Restrictions on the complexity of the problem: Not more than 68 group in the fast group calculation, and not more than 20 regions in the resonance integral calculation. Typical running time: It varies with the number of energy groups and the selection of the geometry. Unusual features of the program: Any or any combination of constituent subprograms can be used so that the partial use of this program is available. (author)

Optimizing Probability of Detection Point Estimate Demonstration

Science.gov (United States)

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.

On the Possibility of Assigning Probabilities to Singular Cases, or: Probability Is Subjective Too!

Directory of Open Access Journals (Sweden)

Mark R. Crovelli

2009-06-01

Full Text Available Both Ludwig von Mises and Richard von Mises claimed that numerical probability could not be legitimately applied to singular cases. This paper challenges this aspect of the von Mises brothers’ theory of probability. It is argued that their denial that numerical probability could be applied to singular cases was based solely upon Richard von Mises’ exceptionally restrictive definition of probability. This paper challenges Richard von Mises’ definition of probability by arguing that the definition of probability necessarily depends upon whether the world is governed by time-invariant causal laws. It is argued that if the world is governed by time-invariant causal laws, a subjective definition of probability must be adopted. It is further argued that both the nature of human action and the relative frequency method for calculating numerical probabilities both presuppose that the world is indeed governed by time-invariant causal laws. It is finally argued that the subjective definition of probability undercuts the von Mises claim that numerical probability cannot legitimately be applied to singular, non-replicable cases.

Antitrust Enforcement Under Endogenous Fines and Price-Dependent Detection Probabilities

NARCIS (Netherlands)

Houba, H.E.D.; Motchenkova, E.; Wen, Q.

2010-01-01

We analyze the effectiveness of antitrust regulation in a repeated oligopoly model in which both fines and detection probabilities depend on the cartel price. Such fines are closer to actual guidelines than the commonly assumed fixed fines. Under a constant detection probability, we confirm the

A simple method to calculate the influence of dose inhomogeneity and fractionation in normal tissue complication probability evaluation

International Nuclear Information System (INIS)

Begnozzi, L.; Gentile, F.P.; Di Nallo, A.M.; Chiatti, L.; Zicari, C.; Consorti, R.; Benassi, M.

1994-01-01

Since volumetric dose distributions are available with 3-dimensional radiotherapy treatment planning they can be used in statistical evaluation of response to radiation. This report presents a method to calculate the influence of dose inhomogeneity and fractionation in normal tissue complication probability evaluation. The mathematical expression for the calculation of normal tissue complication probability has been derived combining the Lyman model with the histogram reduction method of Kutcher et al. and using the normalized total dose (NTD) instead of the total dose. The fitting of published tolerance data, in case of homogeneous or partial brain irradiation, has been considered. For the same total or partial volume homogeneous irradiation of the brain, curves of normal tissue complication probability have been calculated with fraction size of 1.5 Gy and of 3 Gy instead of 2 Gy, to show the influence of fraction size. The influence of dose distribution inhomogeneity and α/β value has also been simulated: Considering α/β=1.6 Gy or α/β=4.1 Gy for kidney clinical nephritis, the calculated curves of normal tissue complication probability are shown. Combining NTD calculations and histogram reduction techniques, normal tissue complication probability can be estimated taking into account the most relevant contributing factors, including the volume effect. (orig.) [de

Probability for statisticians

CERN Document Server

Shorack, Galen R

2017-01-01

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical statistics. It is recommended to anyone interested in the probability underlying modern statistics, providing a solid grounding in the probabilistic tools and techniques necessary to do theoretical research in statistics. For the teaching of probability theory to post graduate statistics students, this is one of the most attractive books available. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic function presentation. Additionally, there is considerable emphasis placed on the quantile function as well as the distribution function. The bootstrap and trimming are both presented. Martingale coverage includes coverage of censored data martingales. The text includes measure theoretic...

PREDICTION OF RESERVOIR FLOW RATE OF DEZ DAM BY THE PROBABILITY MATRIX METHOD

Directory of Open Access Journals (Sweden)

Mohammad Hashem Kanani

2012-12-01

Full Text Available The data collected from the operation of existing storage reservoirs, could offer valuable information for the better allocation and management of fresh water rates for future use to mitigation droughts effect. In this paper the long-term Dez reservoir (IRAN water rate prediction is presented using probability matrix method. Data is analyzed to find the probability matrix of water rates in Dez reservoir based on the previous history of annual water entrance during the past and present years(40 years. The algorithm developed covers both, the overflow and non-overflow conditions in the reservoir. Result of this study shows that in non-overflow conditions the most exigency case is equal to 75%. This means that, if the reservoir is empty (the stored water is less than 100 MCM this year, it would be also empty by 75% next year. The stored water in the reservoir would be less than 300 MCM by 85% next year if the reservoir is empty this year. This percentage decreases to 70% next year if the water of reservoir is less than 300 MCM this year. The percentage also decreases to 5% next year if the reservoir is full this year. In overflow conditions the most exigency case is equal to 75% again. The reservoir volume would be less than 150 MCM by 90% next year, if it is empty this year. This percentage decreases to 70% if its water volume is less than 300 MCM and 55% if the water volume is less than 500 MCM this year. Result shows that too, if the probability matrix of water rates to a reservoir is multiplied by itself repeatedly; it converges to a constant probability matrix, which could be used to predict the long-term water rate of the reservoir. In other words, the probability matrix of series of water rates is changed to a steady probability matrix in the course of time, which could reflect the hydrological behavior of the watershed and could be easily used for the long-term prediction of water storage in the down stream reservoirs.

Improved method for estimating particle scattering probabilities to finite detectors for Monte Carlo simulation

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

Pre-aggregation for Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

Motivated by the increasing need to analyze complex uncertain multidimensional data (e.g., in order to optimize and personalize location-based services), this paper proposes novel types of {\\em probabilistic} OLAP queries that operate on aggregate values that are probability distributions...... and the techniques to process these queries. The paper also presents the methods for computing the probability distributions, which enables pre-aggregation, and for using the pre-aggregated distributions for further aggregation. In order to achieve good time and space efficiency, the methods perform approximate...... multidimensional data analysis that is considered in this paper (i.e., approximate processing of probabilistic OLAP queries over probability distributions)....

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

NARCIS (Netherlands)

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

Unification of field theory and maximum entropy methods for learning probability densities

Science.gov (United States)

Kinney, Justin B.

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Probability-Based Determination Methods for Service Waiting in Service-Oriented Computing Environments

Science.gov (United States)

Zeng, Sen; Huang, Shuangxi; Liu, Yang

Cooperative business processes (CBP)-based service-oriented enterprise networks (SOEN) are emerging with the significant advances of enterprise integration and service-oriented architecture. The performance prediction and optimization for CBP-based SOEN is very complex. To meet these challenges, one of the key points is to try to reduce an abstract service’s waiting number of its physical services. This paper introduces a probability-based determination method (PBDM) of an abstract service’ waiting number, M l , and time span, τ i , for its physical services. The determination of M i and τ i is according to the physical services’ arriving rule and their overall performance’s distribution functions. In PBDM, the arriving probability of the physical services with the best overall performance value is a pre-defined reliability. PBDM has made use of the information of the physical services’ arriving rule and performance distribution functions thoroughly, which will improve the computational efficiency for the scheme design and performance optimization of the collaborative business processes in service-oriented computing environments.

Unification of field theory and maximum entropy methods for learning probability densities.

Science.gov (United States)

Kinney, Justin B

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Deriving the probability of a linear opinion pooling method being superior to a set of alternatives

International Nuclear Information System (INIS)

Bolger, Donnacha; Houlding, Brett

2017-01-01

Linear opinion pools are a common method for combining a set of distinct opinions into a single succinct opinion, often to be used in a decision making task. In this paper we consider a method, termed the Plug-in approach, for determining the weights to be assigned in this linear pool, in a manner that can be deemed as rational in some sense, while incorporating multiple forms of learning over time into its process. The environment that we consider is one in which every source in the pool is herself a decision maker (DM), in contrast to the more common setting in which expert judgments are amalgamated for use by a single DM. We discuss a simulation study that was conducted to show the merits of our technique, and demonstrate how theoretical probabilistic arguments can be used to exactly quantify the probability of this technique being superior (in terms of a probability density metric) to a set of alternatives. Illustrations are given of simulated proportions converging to these true probabilities in a range of commonly used distributional cases. - Highlights: • A novel context for combination of expert opinion is provided. • A dynamic reliability assessment method is stated, justified by properties and a data study. • The theoretical grounding underlying the data-driven justification is explored. • We conclude with areas for expansion and further relevant research.

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).

An innovative method for offshore wind farm site selection based on the interval number with probability distribution

Science.gov (United States)

Wu, Yunna; Chen, Kaifeng; Xu, Hu; Xu, Chuanbo; Zhang, Haobo; Yang, Meng

2017-12-01

There is insufficient research relating to offshore wind farm site selection in China. The current methods for site selection have some defects. First, information loss is caused by two aspects: the implicit assumption that the probability distribution on the interval number is uniform; and ignoring the value of decision makers' (DMs') common opinion on the criteria information evaluation. Secondly, the difference in DMs' utility function has failed to receive attention. An innovative method is proposed in this article to solve these drawbacks. First, a new form of interval number and its weighted operator are proposed to reflect the uncertainty and reduce information loss. Secondly, a new stochastic dominance degree is proposed to quantify the interval number with a probability distribution. Thirdly, a two-stage method integrating the weighted operator with stochastic dominance degree is proposed to evaluate the alternatives. Finally, a case from China proves the effectiveness of this method.

Implementation of the probability table method in a continuous-energy Monte Carlo code system

International Nuclear Information System (INIS)

Sutton, T.M.; Brown, F.B.

1998-10-01

RACER is a particle-transport Monte Carlo code that utilizes a continuous-energy treatment for neutrons and neutron cross section data. Until recently, neutron cross sections in the unresolved resonance range (URR) have been treated in RACER using smooth, dilute-average representations. This paper describes how RACER has been modified to use probability tables to treat cross sections in the URR, and the computer codes that have been developed to compute the tables from the unresolved resonance parameters contained in ENDF/B data files. A companion paper presents results of Monte Carlo calculations that demonstrate the effect of the use of probability tables versus the use of dilute-average cross sections for the URR. The next section provides a brief review of the probability table method as implemented in the RACER system. The production of the probability tables for use by RACER takes place in two steps. The first step is the generation of probability tables from the nuclear parameters contained in the ENDF/B data files. This step, and the code written to perform it, are described in Section 3. The tables produced are at energy points determined by the ENDF/B parameters and/or accuracy considerations. The tables actually used in the RACER calculations are obtained in the second step from those produced in the first. These tables are generated at energy points specific to the RACER calculation. Section 4 describes this step and the code written to implement it, as well as modifications made to RACER to enable it to use the tables. Finally, some results and conclusions are presented in Section 5

Forest regulation methods and silvicultural systems: what are they?

Science.gov (United States)

Ivan L. Sander; Burnell C. Fischer

1989-01-01

"Forest regulation methods" and "silvicultural systems" are important forest resource management concepts but there is much confusion about them. They often mean different things to different individuals. Confusion exists in part because "forest regulation methods" and "silvicultural systems" often use the same terminology. Also...

Optimum Inductive Methods. A study in Inductive Probability, Bayesian Statistics, and Verisimilitude.

NARCIS (Netherlands)

Festa, Roberto

1992-01-01

According to the Bayesian view, scientific hypotheses must be appraised in terms of their posterior probabilities relative to the available experimental data. Such posterior probabilities are derived from the prior probabilities of the hypotheses by applying Bayes'theorem. One of the most important

New method for extracting tumors in PET/CT images based on the probability distribution

International Nuclear Information System (INIS)

Nitta, Shuhei; Hontani, Hidekata; Hukami, Tadanori

2006-01-01

In this report, we propose a method for extracting tumors from PET/CT images by referring to the probability distribution of pixel values in the PET image. In the proposed method, first, the organs that normally take up fluorodeoxyglucose (FDG) (e.g., the liver, kidneys, and brain) are extracted. Then, the tumors are extracted from the images. The distribution of pixel values in PET images differs in each region of the body. Therefore, the threshold for detecting tumors is adaptively determined by referring to the distribution. We applied the proposed method to 37 cases and evaluated its performance. This report also presents the results of experiments comparing the proposed method and another method in which the pixel values are normalized for extracting tumors. (author)

Transmission probability method for solving neutron transport equation in three-dimensional triangular-z geometry

Energy Technology Data Exchange (ETDEWEB)

Liu Guoming [Department of Nuclear Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)], E-mail: gmliusy@gmail.com; Wu Hongchun; Cao Liangzhi [Department of Nuclear Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

2008-09-15

This paper presents a transmission probability method (TPM) to solve the neutron transport equation in three-dimensional triangular-z geometry. The source within the mesh is assumed to be spatially uniform and isotropic. At the mesh surface, the constant and the simplified P{sub 1} approximation are invoked for the anisotropic angular flux distribution. Based on this model, a code TPMTDT is encoded. It was verified by three 3D Takeda benchmark problems, in which the first two problems are in XYZ geometry and the last one is in hexagonal-z geometry, and an unstructured geometry problem. The results of the present method agree well with those of Monte-Carlo calculation method and Spherical Harmonics (P{sub N}) method.

Bayesian optimization for computationally extensive probability distributions.

Science.gov (United States)

Tamura, Ryo; Hukushima, Koji

2018-01-01

An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.

Joint probability safety assessment for NPP defense infrastructure against extreme external natural hazards

International Nuclear Information System (INIS)

Guilin, L.; Defu, L.; Huajun, L.; Fengqing, W.; Tao, Z.

2012-01-01

With the increasing tendency of natural hazards, the typhoon, hurricane and tropical Cyclone induced surge, wave, precipitation, flood and wind as extreme external loads menacing Nuclear Power Plants (NPP) in coastal and inland provinces of China. For all of planned, designed And constructed NPP the National Nuclear Safety Administration of China and IAEA recommended Probable Maximum Hurricane /Typhoon/(PMH/T), Probable Maximum Storm Surge (PMSS), Probable Maximum Flood (PMF), Design Basis Flood (DBF) as safety regulations for NPP defense infrastructures. This paper discusses the joint probability analysis of simultaneous occurrence typhoon induced extreme external hazards and compare with IAEA 2006-2009 recommended safety regulation design criteria for some NPP defense infrastructures along China coast. (authors)

Method to determine transcriptional regulation pathways in organisms

Science.gov (United States)

Gardner, Timothy S.; Collins, James J.; Hayete, Boris; Faith, Jeremiah

2012-11-06

The invention relates to computer-implemented methods and systems for identifying regulatory relationships between expressed regulating polypeptides and targets of the regulatory activities of such regulating polypeptides. More specifically, the invention provides a new method for identifying regulatory dependencies between biochemical species in a cell. In particular embodiments, provided are computer-implemented methods for identifying a regulatory interaction between a transcription factor and a gene target of the transcription factor, or between a transcription factor and a set of gene targets of the transcription factor. Further provided are genome-scale methods for predicting regulatory interactions between a set of transcription factors and a corresponding set of transcriptional target substrates thereof.

Comparing coefficients of nested nonlinear probability models

DEFF Research Database (Denmark)

Kohler, Ulrich; Karlson, Kristian Bernt; Holm, Anders

2011-01-01

In a series of recent articles, Karlson, Holm and Breen have developed a method for comparing the estimated coeffcients of two nested nonlinear probability models. This article describes this method and the user-written program khb that implements the method. The KHB-method is a general decomposi......In a series of recent articles, Karlson, Holm and Breen have developed a method for comparing the estimated coeffcients of two nested nonlinear probability models. This article describes this method and the user-written program khb that implements the method. The KHB-method is a general...... decomposition method that is unaffected by the rescaling or attenuation bias that arise in cross-model comparisons in nonlinear models. It recovers the degree to which a control variable, Z, mediates or explains the relationship between X and a latent outcome variable, Y*, underlying the nonlinear probability...

Probability of Failure in Random Vibration

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

1988-01-01

Close approximations to the first-passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first-passage probability density function and the distribution function for the time interval spent below a barrier before out......-crossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval and thus for the first-passage probability...

Incorporation of Collision Probability Method in STREAM to Consider Non-uniform Material Composition in Fuel Subregions

International Nuclear Information System (INIS)

Choi, Sooyoung; Choe, Jiwon; Lee, Deokjung

2016-01-01

STREAM uses a pin-based slowing-down method (PSM) which solves pointwise energy slowing-down problems with sub-divided fuel pellet, and shows a great performance in calculating effective cross-section (XS). Various issues in the conventional resonance treatment methods (i.e., approximations on resonance scattering source, resonance interference effect, and intrapellet self-shielding effect) were successfully resolved by PSM. PSM assumes that a fuel rod has a uniform material composition and temperature even though PSM calculates spatially dependent effective XSs of fuel subregions. When the depletion calculation or thermal/hydraulic (T/H) coupling are performed with sub-divided material meshes, each subregion has its own material condition depending on position. It was reported that the treatment of distributed temperature is important to calculate an accurate fuel temperature coefficient (FTC). In order to avoid the approximation in PSM, the collision probability method (CPM) has been incorporated as a calculation option. The resonance treatment method, PSM, used in the transport code STREAM has been enhanced to accurately consider a non-uniform material condition. The method incorporates CPM in computing collision probability of isolated fuel pin. From numerical tests with pin-cell problems, STREAM with the method showed very accurate multiplication factor and FTC results less than 83 pcm and 1.43 % differences from the references, respectively. The original PSM showed larger differences than the proposed method but still has a high accuracy

Incorporation of Collision Probability Method in STREAM to Consider Non-uniform Material Composition in Fuel Subregions

Energy Technology Data Exchange (ETDEWEB)

Choi, Sooyoung; Choe, Jiwon; Lee, Deokjung [UNIST, Ulsan (Korea, Republic of)

2016-10-15

STREAM uses a pin-based slowing-down method (PSM) which solves pointwise energy slowing-down problems with sub-divided fuel pellet, and shows a great performance in calculating effective cross-section (XS). Various issues in the conventional resonance treatment methods (i.e., approximations on resonance scattering source, resonance interference effect, and intrapellet self-shielding effect) were successfully resolved by PSM. PSM assumes that a fuel rod has a uniform material composition and temperature even though PSM calculates spatially dependent effective XSs of fuel subregions. When the depletion calculation or thermal/hydraulic (T/H) coupling are performed with sub-divided material meshes, each subregion has its own material condition depending on position. It was reported that the treatment of distributed temperature is important to calculate an accurate fuel temperature coefficient (FTC). In order to avoid the approximation in PSM, the collision probability method (CPM) has been incorporated as a calculation option. The resonance treatment method, PSM, used in the transport code STREAM has been enhanced to accurately consider a non-uniform material condition. The method incorporates CPM in computing collision probability of isolated fuel pin. From numerical tests with pin-cell problems, STREAM with the method showed very accurate multiplication factor and FTC results less than 83 pcm and 1.43 % differences from the references, respectively. The original PSM showed larger differences than the proposed method but still has a high accuracy.

Determining probabilities of geologic events and processes

International Nuclear Information System (INIS)

Hunter, R.L.; Mann, C.J.; Cranwell, R.M.

1985-01-01

The Environmental Protection Agency has recently published a probabilistic standard for releases of high-level radioactive waste from a mined geologic repository. The standard sets limits for contaminant releases with more than one chance in 100 of occurring within 10,000 years, and less strict limits for releases of lower probability. The standard offers no methods for determining probabilities of geologic events and processes, and no consensus exists in the waste-management community on how to do this. Sandia National Laboratories is developing a general method for determining probabilities of a given set of geologic events and processes. In addition, we will develop a repeatable method for dealing with events and processes whose probability cannot be determined. 22 refs., 4 figs

A discussion on the origin of quantum probabilities

International Nuclear Information System (INIS)

Holik, Federico; Sáenz, Manuel; Plastino, Angel

2014-01-01

We study the origin of quantum probabilities as arising from non-Boolean propositional-operational structures. We apply the method developed by Cox to non distributive lattices and develop an alternative formulation of non-Kolmogorovian probability measures for quantum mechanics. By generalizing the method presented in previous works, we outline a general framework for the deduction of probabilities in general propositional structures represented by lattices (including the non-distributive case). -- Highlights: •Several recent works use a derivation similar to that of R.T. Cox to obtain quantum probabilities. •We apply Cox’s method to the lattice of subspaces of the Hilbert space. •We obtain a derivation of quantum probabilities which includes mixed states. •The method presented in this work is susceptible to generalization. •It includes quantum mechanics and classical mechanics as particular cases

Transition probabilities for atoms

International Nuclear Information System (INIS)

Kim, Y.K.

1980-01-01

Current status of advanced theoretical methods for transition probabilities for atoms and ions is discussed. An experiment on the f values of the resonance transitions of the Kr and Xe isoelectronic sequences is suggested as a test for the theoretical methods

Methodical approaches to development of classification state methods of regulation business activity in fishery

OpenAIRE

She Son Gun

2014-01-01

Approaches to development of classification of the state methods of regulation of economy are considered. On the basis of the provided review the complex method of state regulation of business activity is reasonable. The offered principles allow improving public administration and can be used in industry concepts and state programs on support of small business in fishery.

Precipitation intensity probability distribution modelling for hydrological and construction design purposes

International Nuclear Information System (INIS)

Koshinchanov, Georgy; Dimitrov, Dobri

2008-01-01

The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: - The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; - As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. - Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; - Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; - Next method is considering only

Encounter Probability of Individual Wave Height

DEFF Research Database (Denmark)

Liu, Z.; Burcharth, H. F.

1998-01-01

wave height corresponding to a certain exceedence probability within a structure lifetime (encounter probability), based on the statistical analysis of long-term extreme significant wave height. Then the design individual wave height is calculated as the expected maximum individual wave height...... associated with the design significant wave height, with the assumption that the individual wave heights follow the Rayleigh distribution. However, the exceedence probability of such a design individual wave height within the structure lifetime is unknown. The paper presents a method for the determination...... of the design individual wave height corresponding to an exceedence probability within the structure lifetime, given the long-term extreme significant wave height. The method can also be applied for estimation of the number of relatively large waves for fatigue analysis of constructions....

Applied probability and stochastic processes

CERN Document Server

Sumita, Ushio

1999-01-01

Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...

Maximization of regional probabilities using Optimal Surface Graphs

DEFF Research Database (Denmark)

Arias Lorza, Andres M.; Van Engelen, Arna; Petersen, Jens

2018-01-01

Purpose: We present a segmentation method that maximizes regional probabilities enclosed by coupled surfaces using an Optimal Surface Graph (OSG) cut approach. This OSG cut determines the globally optimal solution given a graph constructed around an initial surface. While most methods for vessel...... wall segmentation only use edge information, we show that maximizing regional probabilities using an OSG improves the segmentation results. We applied this to automatically segment the vessel wall of the carotid artery in magnetic resonance images. Methods: First, voxel-wise regional probability maps...... were obtained using a Support Vector Machine classifier trained on local image features. Then, the OSG segments the regions which maximizes the regional probabilities considering smoothness and topological constraints. Results: The method was evaluated on 49 carotid arteries from 30 subjects...

Generalized Probability-Probability Plots

NARCIS (Netherlands)

Mushkudiani, N.A.; Einmahl, J.H.J.

2004-01-01

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P

Quantum Probabilities as Behavioral Probabilities

Directory of Open Access Journals (Sweden)

Vyacheslav I. Yukalov

2017-03-01

Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.

Probability Aggregates in Probability Answer Set Programming

OpenAIRE

Saad, Emad

2013-01-01

Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...

Introduction to probability theory with contemporary applications

CERN Document Server

Helms, Lester L

2010-01-01

This introduction to probability theory transforms a highly abstract subject into a series of coherent concepts. Its extensive discussions and clear examples, written in plain language, expose students to the rules and methods of probability. Suitable for an introductory probability course, this volume requires abstract and conceptual thinking skills and a background in calculus.Topics include classical probability, set theory, axioms, probability functions, random and independent random variables, expected values, and covariance and correlations. Additional subjects include stochastic process

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2010-01-01

This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties is consistent with a RUM. The choice...... probabilities from the RUM are obtained from the gradient of the CPGF. Mixtures of RUM are characterized by logarithmic mixtures of their associated CPGF. The paper relates CPGF to multivariate extreme value distributions, and reviews and extends methods for constructing generating functions for applications....... The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended to competing risk survival models....

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.

Preliminary studies of the kinetics of a reactor by the probability method; Etude preliminaire de la cinetique d'un reacteur par la methode des probabilites

Energy Technology Data Exchange (ETDEWEB)

Bruna, J G; Brunet, J P; Clouet D' Orval, Ch; Caizergues, R; Verriere, Ph [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1964-07-01

The {alpha} decay constant of prompt neutrons has been studied in the homogeneous plutonium-fueled, light-water-moderated reactor Alecto, by the probability method. In this method, the probability to count one, two,.... neutrons during a given time is measured. The value of {alpha} can be deduced from this measurement, for various subcritical states of the reactor. The experimental results were then compared with values obtained, for the same reactivities, by the pulsed neutron technique. (authors) [French] On a etudie sur Alecto, reacteur homogene au plutonium, modere a l'eau legere, la constante de decroissance {alpha} des neutrons prompts par la methode des probabilites. Celle-ci consiste a mesurer la probabilite de compter un, deux, etc..., neutrons pendant un intervalle de temps donne. On a pu en deduire la valeur de {alpha}, dans divers etats sous-critiques du reacteur. On a compare les resultats experimentaux a d'autres valeurs obtenues, aux memes reactivites, par la methode des neutrons pulses. (auteurs)

Optimization of radiation therapy, III: a method of assessing complication probabilities from dose-volume histograms

International Nuclear Information System (INIS)

Lyman, J.T.; Wolbarst, A.B.

1987-01-01

To predict the likelihood of success of a therapeutic strategy, one must be able to assess the effects of the treatment upon both diseased and healthy tissues. This paper proposes a method for determining the probability that a healthy organ that receives a non-uniform distribution of X-irradiation, heat, chemotherapy, or other agent will escape complications. Starting with any given dose distribution, a dose-cumulative-volume histogram for the organ is generated. This is then reduced by an interpolation scheme (involving the volume-weighting of complication probabilities) to a slightly different histogram that corresponds to the same overall likelihood of complications, but which contains one less step. The procedure is repeated, one step at a time, until there remains a final, single-step histogram, for which the complication probability can be determined. The formalism makes use of a complication response function C(D, V) which, for the given treatment schedule, represents the probability of complications arising when the fraction V of the organ receives dose D and the rest of the organ gets none. Although the data required to generate this function are sparse at present, it should be possible to obtain the necessary information from in vivo and clinical studies. Volume effects are taken explicitly into account in two ways: the precise shape of the patient's histogram is employed in the calculation, and the complication response function is a function of the volume

Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems

International Nuclear Information System (INIS)

Turati, Pietro; Pedroni, Nicola; Zio, Enrico

2016-01-01

The efficient estimation of system reliability characteristics is of paramount importance for many engineering applications. Real world system reliability modeling calls for the capability of treating systems that are: i) dynamic, ii) complex, iii) hybrid and iv) highly reliable. Advanced Monte Carlo (MC) methods offer a way to solve these types of problems, which are feasible according to the potentially high computational costs. In this paper, the REpetitive Simulation Trials After Reaching Thresholds (RESTART) method is employed, extending it to hybrid systems for the first time (to the authors’ knowledge). The estimation accuracy and precision of RESTART highly depend on the choice of the Importance Function (IF) indicating how close the system is to failure: in this respect, proper IFs are here originally proposed to improve the performance of RESTART for the analysis of hybrid systems. The resulting overall simulation approach is applied to estimate the probability of failure of the control system of a liquid hold-up tank and of a pump-valve subsystem subject to degradation induced by fatigue. The results are compared to those obtained by standard MC simulation and by RESTART with classical IFs available in the literature. The comparison shows the improvement in the performance obtained by our approach. - Highlights: • We consider the issue of estimating small failure probabilities in dynamic systems. • We employ the RESTART method to estimate the failure probabilities. • New Importance Functions (IFs) are introduced to increase the method performance. • We adopt two dynamic, hybrid, highly reliable systems as case studies. • A comparison with literature IFs proves the effectiveness of the new IFs.

Pre-Aggregation with Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

2006-01-01

Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributions rather than atomic values. The paper describes how to create probability distributions from base data, and how...... the distributions can be subsequently used in pre-aggregation. Since the probability distributions can become large, we show how to achieve good time and space efficiency by approximating the distributions. We present the results of several experiments that demonstrate the effectiveness of our methods. The work...... is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services. This paper is the first to consider the approximate processing of probabilistic OLAP queries over probability distributions....

Probability Issues in without Replacement Sampling

Science.gov (United States)

Joarder, A. H.; Al-Sabah, W. S.

2007-01-01

Sampling without replacement is an important aspect in teaching conditional probabilities in elementary statistics courses. Different methods proposed in different texts for calculating probabilities of events in this context are reviewed and their relative merits and limitations in applications are pinpointed. An alternative representation of…

Probability of Grounding and Collision Events

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup

1996-01-01

To quantify the risks involved in ship traffic, rational criteria for collision and grounding accidents are developed. This implies that probabilities as well as inherent consequences can be analysed and assessed. The presnt paper outlines a method for evaluation of the probability of ship...

Probability of Grounding and Collision Events

DEFF Research Database (Denmark)

Pedersen, Preben Terndrup

1996-01-01

To quantify the risks involved in ship traffic, rational criteria for collision and grounding accidents have to be developed. This implies that probabilities as well as inherent consequences have to be analyzed and assessed.The present notes outline a method for evaluation of the probability...

Probability and statistics with integrated software routines

CERN Document Server

Deep, Ronald

2005-01-01

Probability & Statistics with Integrated Software Routines is a calculus-based treatment of probability concurrent with and integrated with statistics through interactive, tailored software applications designed to enhance the phenomena of probability and statistics. The software programs make the book unique.The book comes with a CD containing the interactive software leading to the Statistical Genie. The student can issue commands repeatedly while making parameter changes to observe the effects. Computer programming is an excellent skill for problem solvers, involving design, prototyping, data gathering, testing, redesign, validating, etc, all wrapped up in the scientific method.See also: CD to accompany Probability and Stats with Integrated Software Routines (0123694698)* Incorporates more than 1,000 engaging problems with answers* Includes more than 300 solved examples* Uses varied problem solving methods

Negative probability in the framework of combined probability

OpenAIRE

Burgin, Mark

2013-01-01

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of conventional probability. So, it is natural that negative probability also has different axiomatic frameworks. In the previous publications (Burgin, 2009; 2010), negative probability was mathematically formalized and rigorously interpreted in the context of extende...

A comparison of Probability Of Detection (POD) data determined using different statistical methods

Science.gov (United States)

Fahr, A.; Forsyth, D.; Bullock, M.

1993-12-01

Different statistical methods have been suggested for determining probability of detection (POD) data for nondestructive inspection (NDI) techniques. A comparative assessment of various methods of determining POD was conducted using results of three NDI methods obtained by inspecting actual aircraft engine compressor disks which contained service induced cracks. The study found that the POD and 95 percent confidence curves as a function of crack size as well as the 90/95 percent crack length vary depending on the statistical method used and the type of data. The distribution function as well as the parameter estimation procedure used for determining POD and the confidence bound must be included when referencing information such as the 90/95 percent crack length. The POD curves and confidence bounds determined using the range interval method are very dependent on information that is not from the inspection data. The maximum likelihood estimators (MLE) method does not require such information and the POD results are more reasonable. The log-logistic function appears to model POD of hit/miss data relatively well and is easy to implement. The log-normal distribution using MLE provides more realistic POD results and is the preferred method. Although it is more complicated and slower to calculate, it can be implemented on a common spreadsheet program.

The Use of Conditional Probability Integral Transformation Method for Testing Accelerated Failure Time Models

Directory of Open Access Journals (Sweden)

Abdalla Ahmed Abdel-Ghaly

2016-06-01

Full Text Available This paper suggests the use of the conditional probability integral transformation (CPIT method as a goodness of fit (GOF technique in the field of accelerated life testing (ALT, specifically for validating the underlying distributional assumption in accelerated failure time (AFT model. The method is based on transforming the data into independent and identically distributed (i.i.d Uniform (0, 1 random variables and then applying the modified Watson statistic to test the uniformity of the transformed random variables. This technique is used to validate each of the exponential, Weibull and lognormal distributions' assumptions in AFT model under constant stress and complete sampling. The performance of the CPIT method is investigated via a simulation study. It is concluded that this method performs well in case of exponential and lognormal distributions. Finally, a real life example is provided to illustrate the application of the proposed procedure.

Ex Post Regulation as the Method of Sectoral Regulation in Electricity Sector

Directory of Open Access Journals (Sweden)

Rafał Nagaj

2017-10-01

Full Text Available Aim/purpose - The aim of the article is to present the essence of ex post approach to sectoral regulation, to show the advantages and disadvantages of ex post regulation and to answer the question whether it is worth using in the electricity sector. Design/methodology/approach - For this purpose, a critical analysis of expert literature was made and an empirical analysis of countries that have applied ex post regulation in the electricity sector in the European Union. Two research methods were used: a case study and a comparison of changes in price and quality of services. The research period covered the period 2000-2016. Findings - It was found that ex post regulation reduces regulatory costs, does not adversely affect the quality of service and long-term rates, gives businesses the freedom of decision-making and the ability to react quickly to changes in the economy. The main disadvantages of ex post regulation are the tendency for companies to over-estimate bills for consumers, the difficulty of pursuing claims by consumers and the need to shift regulatory risk to consumers. Research implications/limitations - In the paper there was identified a research gap, i.e. the effects of ex post regulation in the electricity sector in European Union countries where such regulation was applied. Identifying the research gap will help us understand what are the advantages and disadvantages of ex post regulation and will create a model for when it is good moment to implement this in the economy. Besides identifying the research gap, further studies will be required over ex post regulation. Originality/value/contribution - The additional value of the paper is the study of ex post regulation, its essence and types. The article analyzed the effects of ex post regulation in the electricity sector and provided valuable insights into the potential risks associated with this approach to economic regulation.

System and method for regulating EGR cooling using a rankine cycle

Science.gov (United States)

Ernst, Timothy C.; Morris, Dave

2015-12-22

This disclosure relates to a waste heat recovery (WHR) system and method for regulating exhaust gas recirculation (EGR) cooling, and more particularly, to a Rankine cycle WHR system and method, including a recuperator bypass arrangement to regulate EGR exhaust gas cooling for engine efficiency improvement and thermal management. This disclosure describes other unique bypass arrangements for increased flexibility in the ability to regulate EGR exhaust gas cooling.

A Bayesian-probability-based method for assigning protein backbone dihedral angles based on chemical shifts and local sequences

Energy Technology Data Exchange (ETDEWEB)

Wang Jun; Liu Haiyan [University of Science and Technology of China, Hefei National Laboratory for Physical Sciences at the Microscale, and Key Laboratory of Structural Biology, School of Life Sciences (China)], E-mail: hyliu@ustc.edu.cn

2007-01-15

Chemical shifts contain substantial information about protein local conformations. We present a method to assign individual protein backbone dihedral angles into specific regions on the Ramachandran map based on the amino acid sequences and the chemical shifts of backbone atoms of tripeptide segments. The method uses a scoring function derived from the Bayesian probability for the central residue of a query tripeptide segment to have a particular conformation. The Ramachandran map is partitioned into representative regions at two levels of resolution. The lower resolution partitioning is equivalent to the conventional definitions of different secondary structure regions on the map. At the higher resolution level, the {alpha} and {beta} regions are further divided into subregions. Predictions are attempted at both levels of resolution. We compared our method with TALOS using the original TALOS database, and obtained comparable results. Although TALOS may produce the best results with currently available databases which are much enlarged, the Bayesian-probability-based approach can provide a quantitative measure for the reliability of predictions.

Convergence of Transition Probability Matrix in CLVMarkov Models

Science.gov (United States)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Survival chance in papillary thyroid cancer in Hungary: individual survival probability estimation using the Markov method

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

Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio

Directory of Open Access Journals (Sweden)

William H. Farmer

2017-10-01

New hydrological insights for the region: Several methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index and geospatial tools (kriging and topological kriging. These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.

Statistical probability tables CALENDF program

International Nuclear Information System (INIS)

Ribon, P.

1989-01-01

The purpose of the probability tables is: - to obtain dense data representation - to calculate integrals by quadratures. They are mainly used in the USA for calculations by Monte Carlo and in the USSR and Europe for self-shielding calculations by the sub-group method. The moment probability tables, in addition to providing a more substantial mathematical basis and calculation methods, are adapted for condensation and mixture calculations, which are the crucial operations for reactor physics specialists. However, their extension is limited by the statistical hypothesis they imply. Efforts are being made to remove this obstacle, at the cost, it must be said, of greater complexity

Knowledge typology for imprecise probabilities.

Energy Technology Data Exchange (ETDEWEB)

Wilson, G. D. (Gregory D.); Zucker, L. J. (Lauren J.)

2002-01-01

When characterizing the reliability of a complex system there are often gaps in the data available for specific subsystems or other factors influencing total system reliability. At Los Alamos National Laboratory we employ ethnographic methods to elicit expert knowledge when traditional data is scarce. Typically, we elicit expert knowledge in probabilistic terms. This paper will explore how we might approach elicitation if methods other than probability (i.e., Dempster-Shafer, or fuzzy sets) prove more useful for quantifying certain types of expert knowledge. Specifically, we will consider if experts have different types of knowledge that may be better characterized in ways other than standard probability theory.

Neutron Flux Interpolation with Finite Element Method in the Nuclear Fuel Cell Calculation using Collision Probability Method

International Nuclear Information System (INIS)

Shafii, M. Ali; Su'ud, Zaki; Waris, Abdul; Kurniasih, Neny; Ariani, Menik; Yulianti, Yanti

2010-01-01

Nuclear reactor design and analysis of next-generation reactors require a comprehensive computing which is better to be executed in a high performance computing. Flat flux (FF) approach is a common approach in solving an integral transport equation with collision probability (CP) method. In fact, the neutron flux distribution is not flat, even though the neutron cross section is assumed to be equal in all regions and the neutron source is uniform throughout the nuclear fuel cell. In non-flat flux (NFF) approach, the distribution of neutrons in each region will be different depending on the desired interpolation model selection. In this study, the linear interpolation using Finite Element Method (FEM) has been carried out to be treated the neutron distribution. The CP method is compatible to solve the neutron transport equation for cylindrical geometry, because the angle integration can be done analytically. Distribution of neutrons in each region of can be explained by the NFF approach with FEM and the calculation results are in a good agreement with the result from the SRAC code. In this study, the effects of the mesh on the k eff and other parameters are investigated.

Method of regulating magnetic field of magnetic pole center

International Nuclear Information System (INIS)

Watanabe, Masao; Yamada, Teruo; Kato, Norihiko; Toda, Yojiro; Kaneda, Yasumasa.

1978-01-01

Purpose: To provide the subject method comprising using a plurality of magnetic metal pieces having different thicknesses, regulating very easily symmetry of the field of the magnetic pole center depending upon the combination of said metal pieces, thereby obtaining a magnetic field of high precision. Method: The regulation of magnetic field at the central part of the magnetic field is not depending only upon processing of the center plug, axial movement of trim coil and ion source but by providing a magnetic metal piece such as an iron ring, primary higher harmonics of the field at the center of the magnetic field can be regulated simply while the position of the ion source slit is on the equipotential surface in the field. (Yoshihara, H.)

[Theory analysis and clinical application of spirit-regulating and pain-relieving acupuncture method].

Science.gov (United States)

Chen, Liang; Tang, Lewei; Du, Huaibin; Zheng, Hui; Liang, Fanrong

2015-04-01

The theoretical foundation and scientific connotation of spirit-regulating and pain-relieving acupuncture method as well as its clinical application for pain are discussed. During spirit regulation, attention should be paid on regulating heart and brain, while acupoints should be selected mainly from the Heart Meridian, Pericardium Meridian and Governor Vessel. It has significant efficacy for refractory pain in clinical treatment. Spirit-regulating and pain-relieving acupuncture method is development of acupuncture treating spirit, and it is an important method for pain in clinic. Improvement on sensitization of pain center and brain function is considered as one of the mechanisms in spirit-regulating and pain-relieving acupuncture method.

Computation of the Complex Probability Function

Energy Technology Data Exchange (ETDEWEB)

Trainer, Amelia Jo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ledwith, Patrick John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-08-22

The complex probability function is important in many areas of physics and many techniques have been developed in an attempt to compute it for some z quickly and e ciently. Most prominent are the methods that use Gauss-Hermite quadrature, which uses the roots of the n^th degree Hermite polynomial and corresponding weights to approximate the complex probability function. This document serves as an overview and discussion of the use, shortcomings, and potential improvements on the Gauss-Hermite quadrature for the complex probability function.

Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

International Nuclear Information System (INIS)

Shafii, Mohammad Ali; Meidianti, Rahma; Wildian,; Fitriyani, Dian; Tongkukut, Seni H. J.; Arkundato, Artoto

2014-01-01

Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation

Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

Energy Technology Data Exchange (ETDEWEB)

Shafii, Mohammad Ali, E-mail: mashafii@fmipa.unand.ac.id; Meidianti, Rahma, E-mail: mashafii@fmipa.unand.ac.id; Wildian,, E-mail: mashafii@fmipa.unand.ac.id; Fitriyani, Dian, E-mail: mashafii@fmipa.unand.ac.id [Department of Physics, Andalas University Padang West Sumatera Indonesia (Indonesia); Tongkukut, Seni H. J. [Department of Physics, Sam Ratulangi University Manado North Sulawesi Indonesia (Indonesia); Arkundato, Artoto [Department of Physics, Jember University Jember East Java Indonesia (Indonesia)

2014-09-30

Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation.

Synthetic risks, risk potency, and carcinogen regulation.

Science.gov (United States)

Viscusi, W K; Hakes, J K

1998-01-01

This article analyzes a comprehensive sample of over 350 chemicals tested for carcinogenicity to assess the determinants of the probability of regulation. Controlling for differences in the risk potency and noncancer risks, synthetic chemicals have a significantly higher probability of regulation overall: this is due to the greater likelihood of U.S. Food and Drug Administration (FDA) regulation. Measures of risk potency increase the probability of regulation by the U.S. Environmental Protection Agency (EPA), have a somewhat weaker positive effect on regulation by the U.S. Occupational Safety and Health Administration (OSHA), and decrease the likelihood of regulation by the FDA. The overall regulatory pattern is one in which the FDA targets synthetic chemicals and chemicals that pose relatively minor cancer risk. The EPA particularly performed more sensibly than many critics have suggested.

Probability

CERN Document Server

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

Rapid, single-step most-probable-number method for enumerating fecal coliforms in effluents from sewage treatment plants

Science.gov (United States)

Munoz, E. F.; Silverman, M. P.

1979-01-01

A single-step most-probable-number method for determining the number of fecal coliform bacteria present in sewage treatment plant effluents is discussed. A single growth medium based on that of Reasoner et al. (1976) and consisting of 5.0 gr. proteose peptone, 3.0 gr. yeast extract, 10.0 gr. lactose, 7.5 gr. NaCl, 0.2 gr. sodium lauryl sulfate, and 0.1 gr. sodium desoxycholate per liter is used. The pH is adjusted to 6.5, and samples are incubated at 44.5 deg C. Bacterial growth is detected either by measuring the increase with time in the electrical impedance ratio between the innoculated sample vial and an uninnoculated reference vial or by visual examination for turbidity. Results obtained by the single-step method for chlorinated and unchlorinated effluent samples are in excellent agreement with those obtained by the standard method. It is suggested that in automated treatment plants impedance ratio data could be automatically matched by computer programs with the appropriate dilution factors and most probable number tables already in the computer memory, with the corresponding result displayed as fecal coliforms per 100 ml of effluent.

Establishment probability in newly founded populations

Directory of Open Access Journals (Sweden)

Gusset Markus

2012-06-01

Full Text Available Abstract Background Establishment success in newly founded populations relies on reaching the established phase, which is defined by characteristic fluctuations of the population’s state variables. Stochastic population models can be used to quantify the establishment probability of newly founded populations; however, so far no simple but robust method for doing so existed. To determine a critical initial number of individuals that need to be released to reach the established phase, we used a novel application of the “Wissel plot”, where –ln(1 – P0(t is plotted against time t. This plot is based on the equation P0t=1–c1e–ω1t, which relates the probability of extinction by time t, P0(t, to two constants: c1 describes the probability of a newly founded population to reach the established phase, whereas ω1 describes the population’s probability of extinction per short time interval once established. Results For illustration, we applied the method to a previously developed stochastic population model of the endangered African wild dog (Lycaon pictus. A newly founded population reaches the established phase if the intercept of the (extrapolated linear parts of the “Wissel plot” with the y-axis, which is –ln(c1, is negative. For wild dogs in our model, this is the case if a critical initial number of four packs, consisting of eight individuals each, are released. Conclusions The method we present to quantify the establishment probability of newly founded populations is generic and inferences thus are transferable to other systems across the field of conservation biology. In contrast to other methods, our approach disaggregates the components of a population’s viability by distinguishing establishment from persistence.

Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

Energy Technology Data Exchange (ETDEWEB)

Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

2012-03-15

Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

International Nuclear Information System (INIS)

Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

2012-01-01

Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

Utilization of transmission probabilities in the calculation of unit-cell by the interface-current method

International Nuclear Information System (INIS)

Queiroz Bogado Leite, S. de.

1989-10-01

A widely used but otherwise physically incorrect assumption in unit-cell calculations by the method of interface currents in cylindrical or spherical geometries, is that of that of isotropic fluxes at the surfaces of the cell annular regions, when computing transmission probabilities. In this work, new interface-current relations are developed without making use of this assumption and the effects on calculated integral parameters are shown for an idealized unit-cell example. (author) [pt

High throughput nonparametric probability density estimation.

Science.gov (United States)

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.

Transmission probability method based on triangle meshes for solving unstructured geometry neutron transport problem

Energy Technology Data Exchange (ETDEWEB)

Wu Hongchun [Nuclear Engineering Department, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China)]. E-mail: hongchun@mail.xjtu.edu.cn; Liu Pingping [Nuclear Engineering Department, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China); Zhou Yongqiang [Nuclear Engineering Department, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China); Cao Liangzhi [Nuclear Engineering Department, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China)

2007-01-15

In the advanced reactor, the fuel assembly or core with unstructured geometry is frequently used and for calculating its fuel assembly, the transmission probability method (TPM) has been used widely. However, the rectangle or hexagon meshes are mainly used in the TPM codes for the normal core structure. The triangle meshes are most useful for expressing the complicated unstructured geometry. Even though finite element method and Monte Carlo method is very good at solving unstructured geometry problem, they are very time consuming. So we developed the TPM code based on the triangle meshes. The TPM code based on the triangle meshes was applied to the hybrid fuel geometry, and compared with the results of the MCNP code and other codes. The results of comparison were consistent with each other. The TPM with triangle meshes would thus be expected to be able to apply to the two-dimensional arbitrary fuel assembly.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

Science.gov (United States)

Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

2012-03-15

To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

Probability sampling design in ethnobotanical surveys of medicinal plants

Directory of Open Access Journals (Sweden)

Mariano Martinez Espinosa

2012-07-01

Full Text Available Non-probability sampling design can be used in ethnobotanical surveys of medicinal plants. However, this method does not allow statistical inferences to be made from the data generated. The aim of this paper is to present a probability sampling design that is applicable in ethnobotanical studies of medicinal plants. The sampling design employed in the research titled "Ethnobotanical knowledge of medicinal plants used by traditional communities of Nossa Senhora Aparecida do Chumbo district (NSACD, Poconé, Mato Grosso, Brazil" was used as a case study. Probability sampling methods (simple random and stratified sampling were used in this study. In order to determine the sample size, the following data were considered: population size (N of 1179 families; confidence coefficient, 95%; sample error (d, 0.05; and a proportion (p, 0.5. The application of this sampling method resulted in a sample size (n of at least 290 families in the district. The present study concludes that probability sampling methods necessarily have to be employed in ethnobotanical studies of medicinal plants, particularly where statistical inferences have to be made using data obtained. This can be achieved by applying different existing probability sampling methods, or better still, a combination of such methods.

Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI

Science.gov (United States)

Liu, Rong

2017-01-01

Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with a power projective base method. Then we were applied a decision-making model, the sequential probability ratio testing (SPRT), for single-trial classification of motor imagery movement events. The unique strength of this proposed classification method lies in its accumulative process, which increases the discriminative power as more and more evidence is observed over time. The properties of the method were illustrated on thirteen subjects' recordings from three datasets. Results showed that our proposed power projective method outperformed two benchmark methods for every subject. Moreover, with sequential classifier, the accuracies across subjects were significantly higher than that with nonsequential ones. The average maximum accuracy of the SPRT method was 84.1%, as compared with 82.3% accuracy for the sequential Bayesian (SB) method. The proposed SPRT method provides an explicit relationship between stopping time, thresholds, and error, which is important for balancing the time-accuracy trade-off. These results suggest SPRT would be useful in speeding up decision-making while trading off errors in BCI. PMID:29348781

A backward Monte Carlo method for efficient computation of runaway probabilities in runaway electron simulation

Science.gov (United States)

Zhang, Guannan; Del-Castillo-Negrete, Diego

2017-10-01

Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.

Inverse probability weighting in STI/HIV prevention research: methods for evaluating social and community interventions

Science.gov (United States)

Lippman, Sheri A.; Shade, Starley B.; Hubbard, Alan E.

2011-01-01

Background Intervention effects estimated from non-randomized intervention studies are plagued by biases, yet social or structural intervention studies are rarely randomized. There are underutilized statistical methods available to mitigate biases due to self-selection, missing data, and confounding in longitudinal, observational data permitting estimation of causal effects. We demonstrate the use of Inverse Probability Weighting (IPW) to evaluate the effect of participating in a combined clinical and social STI/HIV prevention intervention on reduction of incident chlamydia and gonorrhea infections among sex workers in Brazil. Methods We demonstrate the step-by-step use of IPW, including presentation of the theoretical background, data set up, model selection for weighting, application of weights, estimation of effects using varied modeling procedures, and discussion of assumptions for use of IPW. Results 420 sex workers contributed data on 840 incident chlamydia and gonorrhea infections. Participators were compared to non-participators following application of inverse probability weights to correct for differences in covariate patterns between exposed and unexposed participants and between those who remained in the intervention and those who were lost-to-follow-up. Estimators using four model selection procedures provided estimates of intervention effect between odds ratio (OR) .43 (95% CI:.22-.85) and .53 (95% CI:.26-1.1). Conclusions After correcting for selection bias, loss-to-follow-up, and confounding, our analysis suggests a protective effect of participating in the Encontros intervention. Evaluations of behavioral, social, and multi-level interventions to prevent STI can benefit by introduction of weighting methods such as IPW. PMID:20375927

Orthogonal Algorithm of Logic Probability and Syndrome-Testable Analysis

Institute of Scientific and Technical Information of China (English)

无

1990-01-01

A new method,orthogonal algoritm,is presented to compute the logic probabilities(i.e.signal probabilities)accurately,The transfer properties of logic probabilities are studied first,which are useful for the calculation of logic probability of the circuit with random independent inputs.Then the orthogonal algoritm is described to compute the logic probability of Boolean function realized by a combinational circuit.This algorithm can make Boolean function “ORTHOGONAL”so that the logic probabilities can be easily calculated by summing up the logic probabilities of all orthogonal terms of the Booleam function.

Maximum parsimony, substitution model, and probability phylogenetic trees.

Science.gov (United States)

Weng, J F; Thomas, D A; Mareels, I

2011-01-01

The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.

A new method for evaluating the availability, reliability, and maintainability whatever may be the probability law

International Nuclear Information System (INIS)

Doyon, L.R.; CEA Centre d'Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette

1975-01-01

A simple method is presented for computer solving every system model (availability, reliability, and maintenance) with intervals between failures, and time duration for repairs distributed according to any probability law, and for any maintainance policy. A matrix equation is obtained using Markov diagrams. An example is given with the solution by the APAFS program (Algorithme Pour l'Analyse de la Fiabilite des Systemes) [fr

Scaling Qualitative Probability

OpenAIRE

Burgin, Mark

2017-01-01

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...

Critical review of the probability of causation method

International Nuclear Information System (INIS)

Cox, L.A. Jr.; Fiksel, J.R.

1985-01-01

In a more controversial report than the others in the study, the authors use one scientific discipline to review the work of another discipline. Their proposal recognizes the imprecision that develops in moving from group to individual interpretations of causal effects by substituting the term assigned share for probability of causation. The authors conclude that the use of a formula will not provide reliable measures of risk attribution in individual cases. The gap between scientific certainty and assigning shares of responsibility must be filled by subjective value judgments supplied by the scientists. 22 references, 2 figures, 4 tables

Studying Musical and Linguistic Prediction in Comparable Ways: The Melodic Cloze Probability Method.

Science.gov (United States)

Fogel, Allison R; Rosenberg, Jason C; Lehman, Frank M; Kuperberg, Gina R; Patel, Aniruddh D

2015-01-01

Prediction or expectancy is thought to play an important role in both music and language processing. However, prediction is currently studied independently in the two domains, limiting research on relations between predictive mechanisms in music and language. One limitation is a difference in how expectancy is quantified. In language, expectancy is typically measured using the cloze probability task, in which listeners are asked to complete a sentence fragment with the first word that comes to mind. In contrast, previous production-based studies of melodic expectancy have asked participants to sing continuations following only one to two notes. We have developed a melodic cloze probability task in which listeners are presented with the beginning of a novel tonal melody (5-9 notes) and are asked to sing the note they expect to come next. Half of the melodies had an underlying harmonic structure designed to constrain expectations for the next note, based on an implied authentic cadence (AC) within the melody. Each such 'authentic cadence' melody was matched to a 'non-cadential' (NC) melody matched in terms of length, rhythm and melodic contour, but differing in implied harmonic structure. Participants showed much greater consistency in the notes sung following AC vs. NC melodies on average. However, significant variation in degree of consistency was observed within both AC and NC melodies. Analysis of individual melodies suggests that pitch prediction in tonal melodies depends on the interplay of local factors just prior to the target note (e.g., local pitch interval patterns) and larger-scale structural relationships (e.g., melodic patterns and implied harmonic structure). We illustrate how the melodic cloze method can be used to test a computational model of melodic expectation. Future uses for the method include exploring the interplay of different factors shaping melodic expectation, and designing experiments that compare the cognitive mechanisms of prediction in

Use of probability methods in prospecting-exploration in looking for oil. Primeneniye veroyatnostnykh metodov v poiskovo-razvedochnykh rabotakh na neft'

Energy Technology Data Exchange (ETDEWEB)

Kharbukh, Dzh U; Davton, Dzh Kh; Devis, Dzh K

1981-01-01

The experience of using probability methods in different geological conditions on the US territory is generalized. The efficiency of using systems analysis, imitation modeling of prospecting-exploration process and conditions for arrangement of fields, machine processing of data in plotting different types of structural maps, probability forecasting of the presence of fields is shown. Especial attention is focused on nonstructural traps. A brief dictionary of terms is presented used in the mathematical apparatus and the computer in oil geology.

Probability of initiation and extinction in the Mercury Monte Carlo code

Energy Technology Data Exchange (ETDEWEB)

McKinley, M. S.; Brantley, P. S. [Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94551 (United States)

2013-07-01

A Monte Carlo method for computing the probability of initiation has previously been implemented in Mercury. Recently, a new method based on the probability of extinction has been implemented as well. The methods have similarities from counting progeny to cycling in time, but they also have differences such as population control and statistical uncertainty reporting. The two methods agree very well for several test problems. Since each method has advantages and disadvantages, we currently recommend that both methods are used to compute the probability of criticality. (authors)

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Science.gov (United States)

She, Qingshan; Ma, Yuliang; Meng, Ming; Luo, Zhizeng

2015-01-01

Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SVM is proposed by the ranking continuous output and pairwise coupling in this paper. First, two-class posterior probability model is constructed to approximate the posterior probability by the ranking continuous output techniques and Platt's estimating method. Secondly, a solution of multiclass probabilistic outputs for twin SVM is provided by combining every pair of class probabilities according to the method of pairwise coupling. Finally, the proposed method is compared with multiclass SVM and twin SVM via voting, and multiclass posterior probability SVM using different coupling approaches. The efficacy on the classification accuracy and time complexity of the proposed method has been demonstrated by both the UCI benchmark datasets and real world EEG data from BCI Competition IV Dataset 2a, respectively.

Normal probability plots with confidence.

Science.gov (United States)

Chantarangsi, Wanpen; Liu, Wei; Bretz, Frank; Kiatsupaibul, Seksan; Hayter, Anthony J; Wan, Fang

2015-01-01

Normal probability plots are widely used as a statistical tool for assessing whether an observed simple random sample is drawn from a normally distributed population. The users, however, have to judge subjectively, if no objective rule is provided, whether the plotted points fall close to a straight line. In this paper, we focus on how a normal probability plot can be augmented by intervals for all the points so that, if the population distribution is normal, then all the points should fall into the corresponding intervals simultaneously with probability 1-α. These simultaneous 1-α probability intervals provide therefore an objective mean to judge whether the plotted points fall close to the straight line: the plotted points fall close to the straight line if and only if all the points fall into the corresponding intervals. The powers of several normal probability plot based (graphical) tests and the most popular nongraphical Anderson-Darling and Shapiro-Wilk tests are compared by simulation. Based on this comparison, recommendations are given in Section 3 on which graphical tests should be used in what circumstances. An example is provided to illustrate the methods. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Probability density of tunneled carrier states near heterojunctions calculated numerically by the scattering method.

Energy Technology Data Exchange (ETDEWEB)

Wampler, William R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Myers, Samuel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Modine, Normand A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

The energy-dependent probability density of tunneled carrier states for arbitrarily specified longitudinal potential-energy profiles in planar bipolar devices is numerically computed using the scattering method. Results agree accurately with a previous treatment based on solution of the localized eigenvalue problem, where computation times are much greater. These developments enable quantitative treatment of tunneling-assisted recombination in irradiated heterojunction bipolar transistors, where band offsets may enhance the tunneling effect by orders of magnitude. The calculations also reveal the density of non-tunneled carrier states in spatially varying potentials, and thereby test the common approximation of uniform- bulk values for such densities.

Evaluation of probability and hazard in nuclear energy

International Nuclear Information System (INIS)

Novikov, V.Ya.; Romanov, N.L.

1979-01-01

Various methods of evaluation of accident probability on NPP are proposed because of NPP security statistic evaluation unreliability. The conception of subjective probability for quantitative analysis of security and hazard are described. Intrepretation of probability as real faith of an expert is assumed as a basis of the conception. It is suggested to study the event uncertainty in the framework of subjective probability theory which not only permits but demands to take into account expert opinions when evaluating the probability. These subjective expert evaluations effect to a certain extent the calculation of the usual mathematical event probability. The above technique is advantageous to use for consideration of a separate experiment or random event

Statistical benchmarking in utility regulation: Role, standards and methods

International Nuclear Information System (INIS)

Newton Lowry, Mark; Getachew, Lullit

2009-01-01

Statistical benchmarking is being used with increasing frequency around the world in utility rate regulation. We discuss how and where benchmarking is in use for this purpose and the pros and cons of regulatory benchmarking. We then discuss alternative performance standards and benchmarking methods in regulatory applications. We use these to propose guidelines for the appropriate use of benchmarking in the rate setting process. The standards, which we term the competitive market and frontier paradigms, have a bearing on method selection. These along with regulatory experience suggest that benchmarking can either be used for prudence review in regulation or to establish rates or rate setting mechanisms directly

Tracer diffusion in an ordered alloy: application of the path probability and Monte Carlo methods

International Nuclear Information System (INIS)

Sato, Hiroshi; Akbar, S.A.; Murch, G.E.

1984-01-01

Tracer diffusion technique has been extensively utilized to investigate diffusion phenomena and has contributed a great deal to the understanding of the phenomena. However, except for self diffusion and impurity diffusion, the meaning of tracer diffusion is not yet satisfactorily understood. Here we try to extend the understanding to concentrated alloys. Our major interest here is directed towards understanding the physical factors which control diffusion through the comparison of results obtained by the Path Probability Method (PPM) and those by the Monte Carlo simulation method (MCSM). Both the PPM and the MCSM are basically in the same category of statistical mechanical approaches applicable to random processes. The advantage of the Path Probability method in dealing with phenomena which occur in crystalline systems has been well established. However, the approximations which are inevitably introduced to make the analytical treatment tractable, although their meaning may be well-established in equilibrium statistical mechanics, sometimes introduce unwarranted consequences the origin of which is often hard to trace. On the other hand, the MCSM which can be carried out in a parallel fashion to the PPM provides, with care, numerically exact results. Thus a side-by-side comparison can give insight into the effect of approximations in the PPM. It was found that in the pair approximation of the CVM, the distribution in the completely random state is regarded as homogeneous (without fluctuations), and hence, the fluctuation in distribution is not well represented in the PPM. These examples thus show clearly how the comparison of analytical results with carefully carried out calculations by the MCSM guides the progress of theoretical treatments and gives insights into the mechanism of diffusion

Bayesian Probability Theory

Science.gov (United States)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

An Alternative Method to Compute the Bit Error Probability of Modulation Schemes Subject to Nakagami- Fading

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.

Toward a generalized probability theory: conditional probabilities

International Nuclear Information System (INIS)

Cassinelli, G.

1979-01-01

The main mathematical object of interest in the quantum logic approach to the foundations of quantum mechanics is the orthomodular lattice and a set of probability measures, or states, defined by the lattice. This mathematical structure is studied per se, independently from the intuitive or physical motivation of its definition, as a generalized probability theory. It is thought that the building-up of such a probability theory could eventually throw light on the mathematical structure of Hilbert-space quantum mechanics as a particular concrete model of the generalized theory. (Auth.)

Some simple applications of probability models to birth intervals

International Nuclear Information System (INIS)

Shrestha, G.

1987-07-01

An attempt has been made in this paper to apply some simple probability models to birth intervals under the assumption of constant fecundability and varying fecundability among women. The parameters of the probability models are estimated by using the method of moments and the method of maximum likelihood. (author). 9 refs, 2 tabs

A bioinformatic survey of distribution, conservation, and probable functions of LuxR solo regulators in bacteria

Science.gov (United States)

Subramoni, Sujatha; Florez Salcedo, Diana Vanessa; Suarez-Moreno, Zulma R.

2015-01-01

LuxR solo transcriptional regulators contain both an autoinducer binding domain (ABD; N-terminal) and a DNA binding Helix-Turn-Helix domain (HTH; C-terminal), but are not associated with a cognate N-acyl homoserine lactone (AHL) synthase coding gene in the same genome. Although a few LuxR solos have been characterized, their distributions as well as their role in bacterial signal perception and other processes are poorly understood. In this study we have carried out a systematic survey of distribution of all ABD containing LuxR transcriptional regulators (QS domain LuxRs) available in the InterPro database (IPR005143), and identified those lacking a cognate AHL synthase. These LuxR solos were then analyzed regarding their taxonomical distribution, predicted functions of neighboring genes and the presence of complete AHL-QS systems in the genomes that carry them. Our analyses reveal the presence of one or multiple predicted LuxR solos in many proteobacterial genomes carrying QS domain LuxRs, some of them harboring genes for one or more AHL-QS circuits. The presence of LuxR solos in bacteria occupying diverse environments suggests potential ecological functions for these proteins beyond AHL and interkingdom signaling. Based on gene context and the conservation levels of invariant amino acids of ABD, we have classified LuxR solos into functionally meaningful groups or putative orthologs. Surprisingly, putative LuxR solos were also found in a few non-proteobacterial genomes which are not known to carry AHL-QS systems. Multiple predicted LuxR solos in the same genome appeared to have different levels of conservation of invariant amino acid residues of ABD questioning their binding to AHLs. In summary, this study provides a detailed overview of distribution of LuxR solos and their probable roles in bacteria with genome sequence information. PMID:25759807

A bioinformatic survey of distribution, conservation, and probable functions of LuxR solo regulators in bacteria.

Science.gov (United States)

Subramoni, Sujatha; Florez Salcedo, Diana Vanessa; Suarez-Moreno, Zulma R

2015-01-01

LuxR solo transcriptional regulators contain both an autoinducer binding domain (ABD; N-terminal) and a DNA binding Helix-Turn-Helix domain (HTH; C-terminal), but are not associated with a cognate N-acyl homoserine lactone (AHL) synthase coding gene in the same genome. Although a few LuxR solos have been characterized, their distributions as well as their role in bacterial signal perception and other processes are poorly understood. In this study we have carried out a systematic survey of distribution of all ABD containing LuxR transcriptional regulators (QS domain LuxRs) available in the InterPro database (IPR005143), and identified those lacking a cognate AHL synthase. These LuxR solos were then analyzed regarding their taxonomical distribution, predicted functions of neighboring genes and the presence of complete AHL-QS systems in the genomes that carry them. Our analyses reveal the presence of one or multiple predicted LuxR solos in many proteobacterial genomes carrying QS domain LuxRs, some of them harboring genes for one or more AHL-QS circuits. The presence of LuxR solos in bacteria occupying diverse environments suggests potential ecological functions for these proteins beyond AHL and interkingdom signaling. Based on gene context and the conservation levels of invariant amino acids of ABD, we have classified LuxR solos into functionally meaningful groups or putative orthologs. Surprisingly, putative LuxR solos were also found in a few non-proteobacterial genomes which are not known to carry AHL-QS systems. Multiple predicted LuxR solos in the same genome appeared to have different levels of conservation of invariant amino acid residues of ABD questioning their binding to AHLs. In summary, this study provides a detailed overview of distribution of LuxR solos and their probable roles in bacteria with genome sequence information.

A bioinformatic survey of distribution, conservation and probable functions of LuxR solo regulators in bacteria

Directory of Open Access Journals (Sweden)

Sujatha eSubramoni

2015-02-01

Full Text Available LuxR solo transcriptional regulators contain both an autoinducer binding domain (ABD; N-terminal and a DNA binding Helix-Turn-Helix domain (HTH; C-terminal, but are not associated with a cognate N-acyl homoserine lactone (AHL synthase coding gene in the same genome. Although a few LuxR solos have been characterized, their distributions as well as their role in bacterial signal perception and other processes are poorly understood. In this study we have carried out a systematic survey of distribution of all ABD containing LuxR transcriptional regulators (QS domain LuxRs available in the InterPro database (IPR005143, and identified those lacking a cognate AHL synthase. These LuxR solos were then analyzed regarding their taxonomical distribution, predicted functions of neighboring genes and the presence of complete AHL-QS systems in the genomes that carry them. Our analyses reveal the presence of one or multiple predicted LuxR solos in many proteobacterial genomes carrying QS domain LuxRs, some of them harboring genes for one or more AHL-QS circuits. The presence of LuxR solos in bacteria occupying diverse environments suggests potential ecological functions for these proteins beyond AHL and interkingdom signaling. Based on gene context and the conservation levels of invariant amino acids of ABD, we have classified LuxR solos into functionally meaningful groups or putative orthologs. Surprisingly, putative LuxR solos were also found in a few non-proteobacterial genomes which are not known to carry AHL-QS systems. Multiple predicted LuxR solos in the same genome appeared to have different levels of conservation of invariant amino acid residues of ABD questioning their binding to AHLs. In summary, this study provides a detailed overview of distribution of LuxR solos and their probable roles in bacteria with genome sequence information.

Expert estimation of human error probabilities in nuclear power plant operations: a review of probability assessment and scaling

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

Safety evaluation and regulation of chemicals. 2. Impact of regulations - improvement of methods

Energy Technology Data Exchange (ETDEWEB)

Homburger, F [ed.

1985-01-01

This volume assesses the impact of new scientific knowledge on the testing and regulation of chemicals, including food additives, drugs, cosmetics, pesticides, and other commercial substances. Apart from describing the newest tests, regulations, and risk assessment strategies, chapters reflect changes forced by both the growing need for cost containment and the mounting pressure to find alternatives to animal testing. Based on an international congress, the book also brings the advantage of diversity in the background and nationality of the authors, thus allowing a view of central problems according to the different interests of academics, industry scientists, government scientists, and regulators. The book opens with coverage of national and international regulations designed to prevent and control damage to human health and the environment. Topics range from basic problems of policy design and enforcement to the specific requirements for chemical regulation in developing countries. The next chapters cover new tests, systems, and assays used in in vivo safety testing. Readers will find a critical assessment of tests used to determine teratogenicity, mutagenicity, carcinogenicity, neurotoxicity and chemical lethality. Other topics include factors operating in the public perception of chemical hazards, guidelines for decision making in the management and regulation of risks, and future trends in the methodology of safety evaluation. The volume concludes with an overview of in vitro methods for testing hepatotoxicity. Several short-term in vitro test models and limited in vivo bioassays are presented and evaluated in terms of their capacity to substitute for long-term animal studies. Expert and thorough in its coverage, the book offers a wealth of technical and practical information for toxicologists, pharmacologists, industrial policy makers, and government regulators. (orig.). With 67 figs., 34 tabs.

Some uses of predictive probability of success in clinical drug development

Directory of Open Access Journals (Sweden)

Mauro Gasparini

2013-03-01

Full Text Available Predictive probability of success is a (subjective Bayesian evaluation of the prob- ability of a future successful event in a given state of information. In the context of pharmaceutical clinical drug development, successful events relate to the accrual of positive evidence on the therapy which is being developed, like demonstration of su- perior efficacy or ascertainment of safety. Positive evidence will usually be obtained via standard frequentist tools, according to the regulations imposed in the world of pharmaceutical development.Within a single trial, predictive probability of success can be identified with expected power, i.e. the evaluation of the success probability of the trial. Success means, for example, obtaining a significant result of a standard superiority test.Across trials, predictive probability of success can be the probability of a successful completion of an entire part of clinical development, for example a successful phase III development in the presence of phase II data.Calculations of predictive probability of success in the presence of normal data with known variance will be illustrated, both for within-trial and across-trial predictions.

Cross Check of NOvA Oscillation Probabilities

Energy Technology Data Exchange (ETDEWEB)

Parke, Stephen J. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States). Dept. of Theoretical Physics; Messier, Mark D. [Indiana Univ., Bloomington, IN (United States). Dept. of Physics

2018-01-12

In this note we perform a cross check of the programs used by NOvA to calculate the 3-flavor oscillation probabilities with a independent program using a different method. The comparison is performed at 6 significant figures and the agreement, $|\\Delta P|/P$ is better than $10^{-5}$, as good as can be expected with 6 significant figures. In addition, a simple and accurate alternative method to calculate the oscillation probabilities is outlined and compared in the L/E range and matter density relevant for the NOvA experiment.

The probability of the false vacuum decay

International Nuclear Information System (INIS)

Kiselev, V.; Selivanov, K.

1983-01-01

The closed expession for the probability of the false vacuum decay in (1+1) dimensions is given. The probability of false vacuum decay is expessed as the product of exponential quasiclassical factor and a functional determinant of the given form. The method for calcutation of this determinant is developed and a complete answer for (1+1) dimensions is given

An Estimation of Human Error Probability of Filtered Containment Venting System Using Dynamic HRA Method

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.

Quantum probability measures and tomographic probability densities

NARCIS (Netherlands)

Amosov, GG; Man'ko, [No Value

2004-01-01

Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the

26 CFR 1.852-2 - Method of taxation of regulated investment companies.

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Method of taxation of regulated investment... Trusts § 1.852-2 Method of taxation of regulated investment companies. (a) Imposition of normal tax and... for partially tax-exempt interest provided by section 242. (b) Taxation of capital gains—(1) In...

Failure probability analysis of optical grid

Science.gov (United States)

Zhong, Yaoquan; Guo, Wei; Sun, Weiqiang; Jin, Yaohui; Hu, Weisheng

2008-11-01

Optical grid, the integrated computing environment based on optical network, is expected to be an efficient infrastructure to support advanced data-intensive grid applications. In optical grid, the faults of both computational and network resources are inevitable due to the large scale and high complexity of the system. With the optical network based distributed computing systems extensive applied in the processing of data, the requirement of the application failure probability have been an important indicator of the quality of application and an important aspect the operators consider. This paper will present a task-based analysis method of the application failure probability in optical grid. Then the failure probability of the entire application can be quantified, and the performance of reducing application failure probability in different backup strategies can be compared, so that the different requirements of different clients can be satisfied according to the application failure probability respectively. In optical grid, when the application based DAG (directed acyclic graph) is executed in different backup strategies, the application failure probability and the application complete time is different. This paper will propose new multi-objective differentiated services algorithm (MDSA). New application scheduling algorithm can guarantee the requirement of the failure probability and improve the network resource utilization, realize a compromise between the network operator and the application submission. Then differentiated services can be achieved in optical grid.

Risk Profile Indicators and Spanish Banks’ Probability of Default from a Regulatory Approach

Directory of Open Access Journals (Sweden)

Pilar Gómez-Fernández-Aguado

2018-04-01

Full Text Available This paper analyses the relationships between the traditional bank risk profile indicators and a new measure of banks’ probability of default that considers the Basel regulatory framework. First, based on the SYstemic Model of Bank Originated Losses (SYMBOL, we calculated the individual probabilities of default (PD of a representative sample of Spanish credit institutions during the period of 2008–2016. Then, panel data regressions were estimated to explore the influence of the risk indicators on the PD. Our findings on the Spanish banking system could be important to regulatory and supervisory authorities. First, the PD based on the SYMBOL model could be used to analyse bank risk from a regulatory approach. Second, the results might be useful for designing new regulations focused on the key factors that affect the banks’ probability of default. Third, our findings reveal that the emphasis on regulation and supervision should differ by type of entity.

Probability of identification (POI): a statistical model for the validation of qualitative botanical identification methods

Science.gov (United States)

A qualitative botanical identification method (BIM) is an analytical procedure which returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) mate...

On Probability Leakage

OpenAIRE

Briggs, William M.

2012-01-01

The probability leakage of model M with respect to evidence E is defined. Probability leakage is a kind of model error. It occurs when M implies that events $y$, which are impossible given E, have positive probability. Leakage does not imply model falsification. Models with probability leakage cannot be calibrated empirically. Regression models, which are ubiquitous in statistical practice, often evince probability leakage.

Selection of risk reduction portfolios under interval-valued probabilities

International Nuclear Information System (INIS)

Toppila, Antti; Salo, Ahti

2017-01-01

A central problem in risk management is that of identifying the optimal combination (or portfolio) of improvements that enhance the reliability of the system most through reducing failure event probabilities, subject to the availability of resources. This optimal portfolio can be sensitive with regard to epistemic uncertainties about the failure events' probabilities. In this paper, we develop an optimization model to support the allocation of resources to improvements that mitigate risks in coherent systems in which interval-valued probabilities defined by lower and upper bounds are employed to capture epistemic uncertainties. Decision recommendations are based on portfolio dominance: a resource allocation portfolio is dominated if there exists another portfolio that improves system reliability (i) at least as much for all feasible failure probabilities and (ii) strictly more for some feasible probabilities. Based on non-dominated portfolios, recommendations about improvements to implement are derived by inspecting in how many non-dominated portfolios a given improvement is contained. We present an exact method for computing the non-dominated portfolios. We also present an approximate method that simplifies the reliability function using total order interactions so that larger problem instances can be solved with reasonable computational effort. - Highlights: • Reliability allocation under epistemic uncertainty about probabilities. • Comparison of alternatives using dominance. • Computational methods for generating the non-dominated alternatives. • Deriving decision recommendations that are robust with respect to epistemic uncertainty.

Estimating the Probability of Wind Ramping Events: A Data-driven Approach

OpenAIRE

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.

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

Joint Probability-Based Neuronal Spike Train Classification

Directory of Open Access Journals (Sweden)

Yan Chen

2009-01-01

Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

Generating prior probabilities for classifiers of brain tumours using belief networks

Directory of Open Access Journals (Sweden)

Arvanitis Theodoros N

2007-09-01

Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

A Method to Estimate the Probability that Any Individual Cloud-to-Ground Lightning Stroke was Within Any Radius of Any Point

Science.gov (United States)

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.

Reliability of structures by using probability and fatigue theories

International Nuclear Information System (INIS)

Lee, Ouk Sub; Kim, Dong Hyeok; Park, Yeon Chang

2008-01-01

Methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluated with the help of the fatigue crack growth models suggested by Paris and Walker. The probability theories such as the FORM (first order reliability method), the SORM (second order reliability method) and the MCS (Monte Carlo simulation) are utilized. It is found that the failure probability decreases with the increase of the design fatigue life and the applied minimum stress, the decrease of the initial edge crack size, the applied maximum stress and the slope of Paris equation. Furthermore, according to the sensitivity analysis of random variables, the slope of Pairs equation affects the failure probability dominantly among other random variables in the Paris and the Walker models

A research on the importance function used in the calculation of the fracture probability through the optimum method

International Nuclear Information System (INIS)

Zegong, Zhou; Changhong, Liu

1995-01-01

On the basis of the research into original distribution function as the importance function after shifting an appropriate distance, this paper takes the variation of similar ratio of the original function to the importance function as the objective function, the optimum shifting distance obtained by use of an optimization method. The optimum importance function resulting from the optimization method can ensure that the number of Monte Carlo simulations is decreased and at the same time the good estimates of the yearly failure probabilities are obtained

DECOFF Probabilities of Failed Operations

DEFF Research Database (Denmark)

Gintautas, Tomas

2015-01-01

A statistical procedure of estimation of Probabilities of Failed Operations is described and exemplified using ECMWF weather forecasts and SIMO output from Rotor Lift test case models. Also safety factor influence is investigated. DECOFF statistical method is benchmarked against standard Alpha-factor...

Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

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.

Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

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.

Fixation probability on clique-based graphs

Science.gov (United States)

Choi, Jeong-Ok; Yu, Unjong

2018-02-01

The fixation probability of a mutant in the evolutionary dynamics of Moran process is calculated by the Monte-Carlo method on a few families of clique-based graphs. It is shown that the complete suppression of fixation can be realized with the generalized clique-wheel graph in the limit of small wheel-clique ratio and infinite size. The family of clique-star is an amplifier, and clique-arms graph changes from amplifier to suppressor as the fitness of the mutant increases. We demonstrate that the overall structure of a graph can be more important to determine the fixation probability than the degree or the heat heterogeneity. The dependence of the fixation probability on the position of the first mutant is discussed.

Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

International Nuclear Information System (INIS)

Vourdas, A.

2014-01-01

The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H 1 ,H 2 ), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H 1 ),P(H 2 ), to the subspaces H 1 , H 2 . As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities

Non-stationary random vibration analysis of a 3D train-bridge system using the probability density evolution method

Science.gov (United States)

Yu, Zhi-wu; Mao, Jian-feng; Guo, Feng-qi; Guo, Wei

2016-03-01

Rail irregularity is one of the main sources causing train-bridge random vibration. A new random vibration theory for the coupled train-bridge systems is proposed in this paper. First, number theory method (NTM) with 2N-dimensional vectors for the stochastic harmonic function (SHF) of rail irregularity power spectrum density was adopted to determine the representative points of spatial frequencies and phases to generate the random rail irregularity samples, and the non-stationary rail irregularity samples were modulated with the slowly varying function. Second, the probability density evolution method (PDEM) was employed to calculate the random dynamic vibration of the three-dimensional (3D) train-bridge system by a program compiled on the MATLAB® software platform. Eventually, the Newmark-β integration method and double edge difference method of total variation diminishing (TVD) format were adopted to obtain the mean value curve, the standard deviation curve and the time-history probability density information of responses. A case study was presented in which the ICE-3 train travels on a three-span simply-supported high-speed railway bridge with excitation of random rail irregularity. The results showed that compared to the Monte Carlo simulation, the PDEM has higher computational efficiency for the same accuracy, i.e., an improvement by 1-2 orders of magnitude. Additionally, the influences of rail irregularity and train speed on the random vibration of the coupled train-bridge system were discussed.

Refinement of a Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

Science.gov (United States)

Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel; Chen, Li

2012-01-01

To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.

PROBABILITY SURVEYS , CONDITIONAL PROBABILITIES AND ECOLOGICAL RISK ASSESSMENT

Science.gov (United States)

We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...

Paradoxes in probability theory

CERN Document Server

Eckhardt, William

2013-01-01

Paradoxes provide a vehicle for exposing misinterpretations and misapplications of accepted principles. This book discusses seven paradoxes surrounding probability theory.  Some remain the focus of controversy; others have allegedly been solved, however the accepted solutions are demonstrably incorrect. Each paradox is shown to rest on one or more fallacies.  Instead of the esoteric, idiosyncratic, and untested methods that have been brought to bear on these problems, the book invokes uncontroversial probability principles, acceptable both to frequentists and subjectivists. The philosophical disputation inspired by these paradoxes is shown to be misguided and unnecessary; for instance, startling claims concerning human destiny and the nature of reality are directly related to fallacious reasoning in a betting paradox, and a problem analyzed in philosophy journals is resolved by means of a computer program.

Collective probabilities algorithm for surface hopping calculations

International Nuclear Information System (INIS)

Bastida, Adolfo; Cruz, Carlos; Zuniga, Jose; Requena, Alberto

2003-01-01

General equations that transition probabilities of the hopping algorithms in surface hopping calculations must obey to assure the equality between the average quantum and classical populations are derived. These equations are solved for two particular cases. In the first it is assumed that probabilities are the same for all trajectories and that the number of hops is kept to a minimum. These assumptions specify the collective probabilities (CP) algorithm, for which the transition probabilities depend on the average populations for all trajectories. In the second case, the probabilities for each trajectory are supposed to be completely independent of the results from the other trajectories. There is, then, a unique solution of the general equations assuring that the transition probabilities are equal to the quantum population of the target state, which is referred to as the independent probabilities (IP) algorithm. The fewest switches (FS) algorithm developed by Tully is accordingly understood as an approximate hopping algorithm which takes elements from the accurate CP and IP solutions. A numerical test of all these hopping algorithms is carried out for a one-dimensional two-state problem with two avoiding crossings which shows the accuracy and computational efficiency of the collective probabilities algorithm proposed, the limitations of the FS algorithm and the similarity between the results offered by the IP algorithm and those obtained with the Ehrenfest method

Time Dependence of Collision Probabilities During Satellite Conjunctions

Science.gov (United States)

Hall, Doyle T.; Hejduk, Matthew D.; Johnson, Lauren C.

2017-01-01

The NASA Conjunction Assessment Risk Analysis (CARA) team has recently implemented updated software to calculate the probability of collision (P (sub c)) for Earth-orbiting satellites. The algorithm can employ complex dynamical models for orbital motion, and account for the effects of non-linear trajectories as well as both position and velocity uncertainties. This “3D P (sub c)” method entails computing a 3-dimensional numerical integral for each estimated probability. Our analysis indicates that the 3D method provides several new insights over the traditional “2D P (sub c)” method, even when approximating the orbital motion using the relatively simple Keplerian two-body dynamical model. First, the formulation provides the means to estimate variations in the time derivative of the collision probability, or the probability rate, R (sub c). For close-proximity satellites, such as those orbiting in formations or clusters, R (sub c) variations can show multiple peaks that repeat or blend with one another, providing insight into the ongoing temporal distribution of risk. For single, isolated conjunctions, R (sub c) analysis provides the means to identify and bound the times of peak collision risk. Additionally, analysis of multiple actual archived conjunctions demonstrates that the commonly used “2D P (sub c)” approximation can occasionally provide inaccurate estimates. These include cases in which the 2D method yields negligibly small probabilities (e.g., P (sub c)) is greater than 10 (sup -10)), but the 3D estimates are sufficiently large to prompt increased monitoring or collision mitigation (e.g., P (sub c) is greater than or equal to 10 (sup -5)). Finally, the archive analysis indicates that a relatively efficient calculation can be used to identify which conjunctions will have negligibly small probabilities. This small-P (sub c) screening test can significantly speed the overall risk analysis computation for large numbers of conjunctions.

On the method of logarithmic cumulants for parametric probability density function estimation.

Science.gov (United States)

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.

Escape and transmission probabilities in cylindrical geometry

International Nuclear Information System (INIS)

Bjerke, M.A.

1980-01-01

An improved technique for the generation of escape and transmission probabilities in cylindrical geometry was applied to the existing resonance cross section processing code ROLAIDS. The algorithm of Hwang and Toppel, [ANL-FRA-TM-118] (with modifications) was employed. The probabilities generated were found to be as accurate as those given by the method previously applied in ROLAIDS, while requiring much less computer core storage and CPU time

Probability an introduction

CERN Document Server

Goldberg, Samuel

1960-01-01

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.

Swedish earthquakes and acceleration probabilities

International Nuclear Information System (INIS)

Slunga, R.

1979-03-01

A method to assign probabilities to ground accelerations for Swedish sites is described. As hardly any nearfield instrumental data is available we are left with the problem of interpreting macroseismic data in terms of acceleration. By theoretical wave propagation computations the relation between seismic strength of the earthquake, focal depth, distance and ground accelerations are calculated. We found that most Swedish earthquake of the area, the 1904 earthquake 100 km south of Oslo, is an exception and probably had a focal depth exceeding 25 km. For the nuclear power plant sites an annual probability of 10 -5 has been proposed as interesting. This probability gives ground accelerations in the range 5-20 % for the sites. This acceleration is for a free bedrock site. For consistency all acceleration results in this study are given for bedrock sites. When applicating our model to the 1904 earthquake and assuming the focal zone to be in the lower crust we get the epicentral acceleration of this earthquake to be 5-15 % g. The results above are based on an analyses of macrosismic data as relevant instrumental data is lacking. However, the macroseismic acceleration model deduced in this study gives epicentral ground acceleration of small Swedish earthquakes in agreement with existent distant instrumental data. (author)

Probability of misclassifying biological elements in surface waters.

Science.gov (United States)

Loga, Małgorzata; Wierzchołowska-Dziedzic, Anna

2017-11-24

Measurement uncertainties are inherent to assessment of biological indices of water bodies. The effect of these uncertainties on the probability of misclassification of ecological status is the subject of this paper. Four Monte-Carlo (M-C) models were applied to simulate the occurrence of random errors in the measurements of metrics corresponding to four biological elements of surface waters: macrophytes, phytoplankton, phytobenthos, and benthic macroinvertebrates. Long series of error-prone measurement values of these metrics, generated by M-C models, were used to identify cases in which values of any of the four biological indices lay outside of the "true" water body class, i.e., outside the class assigned from the actual physical measurements. Fraction of such cases in the M-C generated series was used to estimate the probability of misclassification. The method is particularly useful for estimating the probability of misclassification of the ecological status of surface water bodies in the case of short sequences of measurements of biological indices. The results of the Monte-Carlo simulations show a relatively high sensitivity of this probability to measurement errors of the river macrophyte index (MIR) and high robustness to measurement errors of the benthic macroinvertebrate index (MMI). The proposed method of using Monte-Carlo models to estimate the probability of misclassification has significant potential for assessing the uncertainty of water body status reported to the EC by the EU member countries according to WFD. The method can be readily applied also in risk assessment of water management decisions before adopting the status dependent corrective actions.

Visualization techniques for spatial probability density function data

Directory of Open Access Journals (Sweden)

Udeepta D Bordoloi

2006-01-01

Full Text Available Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data. The clustering methods are used on two datasets, and the results are discussed with the help of visualization techniques designed for the spatial probability data.

Probability 1/e

Science.gov (United States)

Koo, Reginald; Jones, Martin L.

2011-01-01

Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.

Fisher classifier and its probability of error estimation

Science.gov (United States)

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.

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)

The probability factor in establishing causation

International Nuclear Information System (INIS)

Hebert, J.

1988-01-01

This paper discusses the possibilities and limitations of methods using the probability factor in establishing the causal link between bodily injury, whether immediate or delayed, and the nuclear incident presumed to have caused it (NEA) [fr

An Alternative Teaching Method of Conditional Probabilities and Bayes' Rule: An Application of the Truth Table

Science.gov (United States)

Satake, Eiki; Vashlishan Murray, Amy

2015-01-01

This paper presents a comparison of three approaches to the teaching of probability to demonstrate how the truth table of elementary mathematical logic can be used to teach the calculations of conditional probabilities. Students are typically introduced to the topic of conditional probabilities--especially the ones that involve Bayes' rule--with…

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

Science.gov (United States)

Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K; Kalinin, Alexandr; Christou, Nicolas

2016-06-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome , which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the

Using inferred probabilities to measure the accuracy of imprecise forecasts

Directory of Open Access Journals (Sweden)

Paul Lehner

2012-11-01

Full Text Available Research on forecasting is effectively limited to forecasts that are expressed with clarity; which is to say that the forecasted event must be sufficiently well-defined so that it can be clearly resolved whether or not the event occurred and forecasts certainties are expressed as quantitative probabilities. When forecasts are expressed with clarity, then quantitative measures (scoring rules, calibration, discrimination, etc. can be used to measure forecast accuracy, which in turn can be used to measure the comparative accuracy of different forecasting methods. Unfortunately most real world forecasts are not expressed clearly. This lack of clarity extends to both the description of the forecast event and to the use of vague language to express forecast certainty. It is thus difficult to assess the accuracy of most real world forecasts, and consequently the accuracy the methods used to generate real world forecasts. This paper addresses this deficiency by presenting an approach to measuring the accuracy of imprecise real world forecasts using the same quantitative metrics routinely used to measure the accuracy of well-defined forecasts. To demonstrate applicability, the Inferred Probability Method is applied to measure the accuracy of forecasts in fourteen documents examining complex political domains. Key words: inferred probability, imputed probability, judgment-based forecasting, forecast accuracy, imprecise forecasts, political forecasting, verbal probability, probability calibration.

Internal Medicine residents use heuristics to estimate disease probability

OpenAIRE

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...

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

Science.gov (United States)

Generazio, Edward R.

2011-01-01

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Foundations of probability

International Nuclear Information System (INIS)

Fraassen, B.C. van

1979-01-01

The interpretation of probabilities in physical theories are considered, whether quantum or classical. The following points are discussed 1) the functions P(μ, Q) in terms of which states and propositions can be represented, are classical (Kolmogoroff) probabilities, formally speaking, 2) these probabilities are generally interpreted as themselves conditional, and the conditions are mutually incompatible where the observables are maximal and 3) testing of the theory typically takes the form of confronting the expectation values of observable Q calculated with probability measures P(μ, Q) for states μ; hence, of comparing the probabilities P(μ, Q)(E) with the frequencies of occurrence of the corresponding events. It seems that even the interpretation of quantum mechanics, in so far as it concerns what the theory says about the empirical (i.e. actual, observable) phenomena, deals with the confrontation of classical probability measures with observable frequencies. This confrontation is studied. (Auth./C.F.)

Non-Archimedean Probability

NARCIS (Netherlands)

Benci, Vieri; Horsten, Leon; Wenmackers, Sylvia

We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned

Exact asymptotics of probabilities of large deviations for Markov chains: the Laplace method

Energy Technology Data Exchange (ETDEWEB)

Fatalov, Vadim R [M. V. Lomonosov Moscow State University, Faculty of Mechanics and Mathematics, Moscow (Russian Federation)

2011-08-31

We prove results on exact asymptotics as n{yields}{infinity} for the expectations E{sub a} exp{l_brace}-{theta}{Sigma}{sub k=0}{sup n-1}g(X{sub k}){r_brace} and probabilities P{sub a}{l_brace}(1/n {Sigma}{sub k=0}{sup n-1}g(X{sub k})=}1, is the corresponding random walk on R, g(x) is a positive continuous function satisfying certain conditions, and d>0, {theta}>0, a element of R are fixed numbers. Our results are obtained using a new method which is developed in this paper: the Laplace method for the occupation time of discrete-time Markov chains. For g(x) one can take |x|{sup p}, log (|x|{sup p}+1), p>0, |x| log (|x|+1), or e{sup {alpha}|x|}-1, 0<{alpha}<1/2, x element of R, for example. We give a detailed treatment of the case when g(x)=|x| using Bessel functions to make explicit calculations.

Electrofishing capture probability of smallmouth bass in streams

Science.gov (United States)

Dauwalter, D.C.; Fisher, W.L.

2007-01-01

Abundance estimation is an integral part of understanding the ecology and advancing the management of fish populations and communities. Mark-recapture and removal methods are commonly used to estimate the abundance of stream fishes. Alternatively, abundance can be estimated by dividing the number of individuals sampled by the probability of capture. We conducted a mark-recapture study and used multiple repeated-measures logistic regression to determine the influence of fish size, sampling procedures, and stream habitat variables on the cumulative capture probability for smallmouth bass Micropterus dolomieu in two eastern Oklahoma streams. The predicted capture probability was used to adjust the number of individuals sampled to obtain abundance estimates. The observed capture probabilities were higher for larger fish and decreased with successive electrofishing passes for larger fish only. Model selection suggested that the number of electrofishing passes, fish length, and mean thalweg depth affected capture probabilities the most; there was little evidence for any effect of electrofishing power density and woody debris density on capture probability. Leave-one-out cross validation showed that the cumulative capture probability model predicts smallmouth abundance accurately. ?? Copyright by the American Fisheries Society 2007.

Initial state regulation of investor-owned utilities

International Nuclear Information System (INIS)

Savitski, D.W.

2001-01-01

This paper examines state initiation of public service (or utility) commission regulation of investor-owned utilities (IOUs) using an economic theory of regulation. The decision to regulate IOUs is assumed to have depended on the strength of competing interest groups, e.g. consumers and producers, and on institutional factors, e.g. whether commissioners were appointed or elected. Regulators, which then had jurisdiction over IOU rates, are assumed to have been optimizing agents. The potential benefits of regulation, in turn, translated into pressure to initiate regulation. To test this, a hazard model is applied to state-level data. On the demand side of the regulation market, the distribution of federal power and population density were unrelated, while a set of time dummies was positively related to the probability that a state initiated regulation. On the supply side, the fraction of the population that was urban and whether the governor was Republican or not were positively and negatively related to this probability

Handbook of probability

CERN Document Server

Florescu, Ionut

2013-01-01

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing basic examples throughout, the handbook expertly transitions between concepts and practice to allow readers an inclusive introduction to the field of probability. The book provides a useful format with self-contained chapters, allowing the reader easy and quick reference. Each chapter includes an introductio

Probability-1

CERN Document Server

Shiryaev, Albert N

2016-01-01

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, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. 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 independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.

Measurement uncertainty and probability

CERN Document Server

Willink, Robin

2013-01-01

A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.

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...

Qualification of the calculational methods of the fluence in the pressurised water reactors. Improvement of the cross sections treatment by the probability table method; Qualification des methodes de calculs de fluence dans les reacteurs a eau pressurisee. Amelioration du traitement des sections efficaces par la methode des tables de probabilite

Energy Technology Data Exchange (ETDEWEB)

Zheng, S H

1994-01-01

It is indispensable to know the fluence on the nuclear reactor pressure vessel. The cross sections and their treatment have an important rule to this problem. In this study, two ``benchmarks`` have been interpreted by the Monte Carlo transport program TRIPOLI to qualify the calculational method and the cross sections used in the calculations. For the treatment of the cross sections, the multigroup method is usually used but it exists some problems such as the difficulty to choose the weighting function and the necessity of a great number of energy to represent well the cross section`s fluctuation. In this thesis, we propose a new method called ``Probability Table Method`` to treat the neutron cross sections. For the qualification, a program of the simulation of neutron transport by the Monte Carlo method in one dimension has been written; the comparison of multigroup`s results and probability table`s results shows the advantages of this new method. The probability table has also been introduced in the TRIPOLI program; the calculational results of the iron deep penetration benchmark has been improved by comparing with the experimental results. So it is interest to use this new method in the shielding and neutronic calculation. (author). 42 refs., 109 figs., 36 tabs.

Probability-density-function characterization of multipartite entanglement

International Nuclear Information System (INIS)

Facchi, P.; Florio, G.; Pascazio, S.

2006-01-01

We propose a method to characterize and quantify multipartite entanglement for pure states. The method hinges upon the study of the probability density function of bipartite entanglement and is tested on an ensemble of qubits in a variety of situations. This characterization is also compared to several measures of multipartite entanglement

Introduction to Probability, Part 1 - Basic Concepts. Student Text. Revised Edition.

Science.gov (United States)

Blakeslee, David W.; And Others

This book is designed to introduce the reader to some fundamental ideas about probability. The mathematical theory of probability plays an increasingly important role in science, government, industry, business, and economics. An understanding of the basic concepts of probability is essential for the study of statistical methods that are widely…

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

Science.gov (United States)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

Prospect evaluation as a function of numeracy and probability denominator.

Science.gov (United States)

Millroth, Philip; Juslin, Peter

2015-05-01

This study examines how numeracy and probability denominator (a direct-ratio probability, a relative frequency with denominator 100, a relative frequency with denominator 10,000) affect the evaluation of prospects in an expected-value based pricing task. We expected that numeracy would affect the results due to differences in the linearity of number perception and the susceptibility to denominator neglect with different probability formats. An analysis with functional measurement verified that participants integrated value and probability into an expected value. However, a significant interaction between numeracy and probability format and subsequent analyses of the parameters of cumulative prospect theory showed that the manipulation of probability denominator changed participants' psychophysical response to probability and value. Standard methods in decision research may thus confound people's genuine risk attitude with their numerical capacities and the probability format used. Copyright © 2015 Elsevier B.V. All rights reserved.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

Science.gov (United States)

Wei, Wei; Larrey-Lassalle, Pyrène; Faure, Thierry; Dumoulin, Nicolas; Roux, Philippe; Mathias, Jean-Denis

2016-03-01

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

Janus-faced probability

CERN Document Server

Rocchi, Paolo

2014-01-01

The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability. Beyond the radical followers of the two schools, a circle of pluralist thinkers tends to reconcile the opposing concepts. The author uses two theorems in order to prove that the various interpretations of probability do not come into opposition and can be used in different contexts. The goal here is to clarify the multifold nature of probability by means of a purely mathematical approach and to show how philosophical arguments can only serve to deepen actual intellectual contrasts. The book can be considered as one of the most important contributions in the analysis of probability interpretation in the last 10-15 years.

Methods to Regulate Unbundled Transmission and Distribution Business on Electricity Markets

International Nuclear Information System (INIS)

Forsberg, Kaj; Fritz, Peter

2003-11-01

The regulation of distribution utilities is evolving from the traditional approach based on a cost of service or rate of return remuneration, to ways of regulation more specifically focused on providing incentives for improving efficiency, known as performance-based regulation or ratemaking. Modern regulation systems are also, to a higher degree than previously, intended to simulate competitive market conditions. The Market Design 2003-conference gathered people from 18 countries to discuss 'Methods to regulate unbundled transmission and distribution business on electricity markets'. Speakers from nine different countries and backgrounds (academics, industry and regulatory) presented their experiences and most recent works on how to make the regulation of unbundled distribution business as accurate as possible. This paper does not claim to be a fully representative summary of everything that was presented or discussed during the conference. Rather, it is a purposely restricted document where we focus on a few central themes and experiences from different countries

Methods to Regulate Unbundled Transmission and Distribution Business on Electricity Markets

Energy Technology Data Exchange (ETDEWEB)

Forsberg, Kaj; Fritz, Peter

2003-11-01

The regulation of distribution utilities is evolving from the traditional approach based on a cost of service or rate of return remuneration, to ways of regulation more specifically focused on providing incentives for improving efficiency, known as performance-based regulation or ratemaking. Modern regulation systems are also, to a higher degree than previously, intended to simulate competitive market conditions. The Market Design 2003-conference gathered people from 18 countries to discuss 'Methods to regulate unbundled transmission and distribution business on electricity markets'. Speakers from nine different countries and backgrounds (academics, industry and regulatory) presented their experiences and most recent works on how to make the regulation of unbundled distribution business as accurate as possible. This paper does not claim to be a fully representative summary of everything that was presented or discussed during the conference. Rather, it is a purposely restricted document where we focus on a few central themes and experiences from different countries.

Quantification of a decision-making failure probability of the accident management using cognitive analysis model

Energy Technology Data Exchange (ETDEWEB)

Yoshida, Yoshitaka; Ohtani, Masanori [Institute of Nuclear Safety System, Inc., Mihama, Fukui (Japan); Fujita, Yushi [TECNOVA Corp., Tokyo (Japan)

2002-09-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

Quantification of a decision-making failure probability of the accident management using cognitive analysis model

International Nuclear Information System (INIS)

Yoshida, Yoshitaka; Ohtani, Masanori; Fujita, Yushi

2002-01-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

A note on the transition probability over Csup(*)-algebras

International Nuclear Information System (INIS)

Alberti, P.M.; Karl-Marx-Universitaet, Leipzig

1983-01-01

The algebraic structure of Uhlmann's transition probability between mixed states on unital Csup(*)-algebras is analyzed. Several improvements of methods to calculate the transition probability are fixed, examples are given (e.g., the case of quasi-local Csup(*)-algebras is dealt with) and two more functional characterizations are proved in general. (orig.)

Statistical validation of normal tissue complication probability models

NARCIS (Netherlands)

Xu, Cheng-Jian; van der Schaaf, Arjen; van t Veld, Aart; Langendijk, Johannes A.; Schilstra, Cornelis

2012-01-01

PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage

Ruin probabilities

DEFF Research Database (Denmark)

Asmussen, Søren; Albrecher, Hansjörg

The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....

Method for assessing the probability of accumulated doses from an intermittent source using the convolution technique

International Nuclear Information System (INIS)

Coleman, J.H.

1980-10-01

A technique is discussed for computing the probability distribution of the accumulated dose received by an arbitrary receptor resulting from several single releases from an intermittent source. The probability density of the accumulated dose is the convolution of the probability densities of doses from the intermittent releases. Emissions are not assumed to be constant over the brief release period. The fast fourier transform is used in the calculation of the convolution

Constructing probability boxes and Dempster-Shafer structures

Energy Technology Data Exchange (ETDEWEB)

Ferson, Scott [Applied Biomathematics, Setauket, NY (United States); Kreinovich, Vladik [Applied Biomathematics, Setauket, NY (United States); Grinzburg, Lev [Applied Biomathematics, Setauket, NY (United States); Myers, Davis [Applied Biomathematics, Setauket, NY (United States); Sentz, Kari [Binghamton Univ., NY (United States). Thomas J. Watson School of Engineering and Applied Science, Systems Science and Industrial Engineering Dept.

2015-05-01

This report summarizes a variety of the most useful and commonly applied methods for obtaining Dempster-Shafer structures, and their mathematical kin probability boxes, from empirical information or theoretical knowledge. The report includes a review of the aggregation methods for handling agreement and conflict when multiple such objects are obtained from different sources.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

Science.gov (United States)

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Interpretations of probability

CERN Document Server

Khrennikov, Andrei

2009-01-01

This is the first fundamental book devoted to non-Kolmogorov probability models. It provides a mathematical theory of negative probabilities, with numerous applications to quantum physics, information theory, complexity, biology and psychology. The book also presents an interesting model of cognitive information reality with flows of information probabilities, describing the process of thinking, social, and psychological phenomena.

Posterior Probability Matching and Human Perceptual Decision Making.

Directory of Open Access Journals (Sweden)

Richard F Murray

2015-06-01

Full Text Available Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models' performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods

Crash probability estimation via quantifying driver hazard perception.

Science.gov (United States)

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.

Men who have sex with men in Great Britain: comparing methods and estimates from probability and convenience sample surveys

Science.gov (United States)

Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H

2016-01-01

Objective To examine sociodemographic and behavioural differences between men who have sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey. Methods We compared 148 MSM aged 18–64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010–2012, with men in the same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European MSM Internet Survey (EMIS); 797 in the London Gay Men's Sexual Health Survey; and 1234 in Scotland's Gay Men's Sexual Health Survey. Analyses compared men reporting at least one male sexual partner (past year) on similarly worded questions and multivariable analyses accounted for sociodemographic differences between the surveys. Results MSM in convenience surveys were younger and better educated than MSM in Natsal-3, and a larger proportion identified as gay (85%–95% vs 62%). Partner numbers were higher and same-sex anal sex more common in convenience surveys. Unprotected anal intercourse was more commonly reported in EMIS. Compared with Natsal-3, MSM in convenience surveys were more likely to report gonorrhoea diagnoses and HIV testing (both past year). Differences between the samples were reduced when restricting analysis to gay-identifying MSM. Conclusions National probability surveys better reflect the population of MSM but are limited by their smaller samples of MSM. Convenience surveys recruit larger samples of MSM but tend to over-represent MSM identifying as gay and reporting more sexual risk behaviours. Because both sampling strategies have strengths and weaknesses, methods are needed to triangulate data from probability and convenience surveys. PMID:26965869

26 CFR 1.852-4 - Method of taxation of shareholders of regulated investment companies.

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Method of taxation of shareholders of regulated investment companies. 1.852-4 Section 1.852-4 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE... Investment Trusts § 1.852-4 Method of taxation of shareholders of regulated investment companies. (a...

Probability and containment of turbine missiles

International Nuclear Information System (INIS)

Yeh, G.C.K.

1976-01-01

With the trend toward ever larger power generating plants with large high-speed turbines, an important plant design consideration is the potential for and consequences of mechanical failure of turbine rotors. Such rotor failure could result in high-velocity disc fragments (turbine missiles) perforating the turbine casing and jeopardizing vital plant systems. The designer must first estimate the probability of any turbine missile damaging any safety-related plant component for his turbine and his plant arrangement. If the probability is not low enough to be acceptable to the regulatory agency, he must design a shield to contain the postulated turbine missiles. Alternatively, the shield could be designed to retard (to reduce the velocity of) the missiles such that they would not damage any vital plant system. In this paper, some of the presently available references that can be used to evaluate the probability, containment and retardation of turbine missiles are reviewed; various alternative methods are compared; and subjects for future research are recommended. (Auth.)

Resveratrol enhances airway surface liquid depth in sinonasal epithelium by increasing cystic fibrosis transmembrane conductance regulator open probability.

Directory of Open Access Journals (Sweden)

Shaoyan Zhang

Full Text Available Chronic rhinosinusitis engenders enormous morbidity in the general population, and is often refractory to medical intervention. Compounds that augment mucociliary clearance in airway epithelia represent a novel treatment strategy for diseases of mucus stasis. A dominant fluid and electrolyte secretory pathway in the nasal airways is governed by the cystic fibrosis transmembrane conductance regulator (CFTR. The objectives of the present study were to test resveratrol, a strong potentiator of CFTR channel open probability, in preparation for a clinical trial of mucociliary activators in human sinus disease.Primary sinonasal epithelial cells, immortalized bronchoepithelial cells (wild type and F508del CFTR, and HEK293 cells expressing exogenous human CFTR were investigated by Ussing chamber as well as patch clamp technique under non-phosphorylating conditions. Effects on airway surface liquid depth were measured using confocal laser scanning microscopy. Impact on CFTR gene expression was measured by quantitative reverse transcriptase polymerase chain reaction.Resveratrol is a robust CFTR channel potentiator in numerous mammalian species. The compound also activated temperature corrected F508del CFTR and enhanced CFTR-dependent chloride secretion in human sinus epithelium ex vivo to an extent comparable to the recently approved CFTR potentiator, ivacaftor. Using inside out patches from apical membranes of murine cells, resveratrol stimulated an ~8 picosiemens chloride channel consistent with CFTR. This observation was confirmed in HEK293 cells expressing exogenous CFTR. Treatment of sinonasal epithelium resulted in a significant increase in airway surface liquid depth (in µm: 8.08+/-1.68 vs. 6.11+/-0.47,control,p<0.05. There was no increase CFTR mRNA.Resveratrol is a potent chloride secretagogue from the mucosal surface of sinonasal epithelium, and hydrates airway surface liquid by increasing CFTR channel open probability. The foundation for a

Hamiltonian theories quantization based on a probability operator

International Nuclear Information System (INIS)

Entral'go, E.E.

1986-01-01

The quantization method with a linear reflection of classical coordinate-momentum-time functions Λ(q,p,t) at quantum operators in a space of quantum states ψ, is considered. The probability operator satisfies a system of equations representing the principles of dynamical and canonical correspondences between the classical and quantum theories. The quantization based on a probability operator leads to a quantum theory with a nonnegative joint coordinate-momentum distribution function for any state ψ. The main consequences of quantum mechanics with a probability operator are discussed in comparison with the generally accepted quantum and classical theories. It is shown that a probability operator leads to an appearance of some new notions called ''subquantum'' ones. Hence the quantum theory with a probability operator does not pretend to any complete description of physical reality in terms of classical variables and by this reason contains no problems like Einstein-Podolsky-Rosen paradox. The results of some concrete problems are given: a free particle, a harmonic oscillator, an electron in the Coulomb field. These results give hope on the possibility of an experimental verification of the quantization based on a probability operator

Risk estimation using probability machines

Science.gov (United States)

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

[CALCULATION OF THE PROBABILITY OF METALS INPUT INTO AN ORGANISM WITH DRINKING POTABLE WATERS].

Science.gov (United States)

Tunakova, Yu A; Fayzullin, R I; Valiev, V S

2015-01-01

The work was performed in framework of the State program for the improvement of the competitiveness of Kazan (Volga) Federal University among the world's leading research and education centers and subsidies unveiled to Kazan Federal University to perform public tasks in the field of scientific research. In the current methodological recommendations "Guide for assessing the risk to public health under the influence of chemicals that pollute the environment," P 2.1.10.1920-04 there is regulated the determination of quantitative and/or qualitative characteristics of the harmful effects to human health from exposure to environmental factors. We proposed to complement the methodological approaches presented in P 2.1.10.1920-04, with the estimation of the probability of pollutants input in the body with drinking water which is the greater, the higher the order of the excess of the actual concentrations of the substances in comparison with background concentrations. In the paper there is proposed a method of calculation of the probability of exceeding the actual concentrations of metal cations above the background in samples of drinking water consumed by the population, which were selected at the end points of consumption in houses and apartments, to accommodate the passage of secondary pollution ofwater pipelines and distributing paths. Research was performed on the example of Kazan, divided into zones. The calculation of probabilities was made with the use of Bayes' theorem.

The probability of a tornado missile hitting a target

International Nuclear Information System (INIS)

Goodman, J.; Koch, J.E.

1983-01-01

It is shown that tornado missile transportation is a diffusion Markovian process. Therefore, the Green's function method is applied for the estimation of the probability of hitting a unit target area. This propability is expressed through a joint density of tornado intensity and path area, a probability of tornado missile injection and a tornado missile height distribution. (orig.)

Apparatus and test method for characterizing the temperature regulating properties of thermal functional porous polymeric materials.

Science.gov (United States)

Yao, Bao-Guo; Zhang, Shan; Zhang, De-Pin

2017-05-01

In order to evaluate the temperature regulating properties of thermal functional porous polymeric materials such as fabrics treated with phase change material microcapsules, a new apparatus was developed. The apparatus and the test method can measure the heat flux, temperature, and displacement signals during the dynamic contact and then quickly give an evaluation for the temperature regulating properties by simulating the dynamic heat transfer and temperature regulating process when the materials contact the body skin. A series of indices including the psychosensory intensity, regulating capability index, and relative regulating index were defined to characterize the temperature regulating properties. The measurement principle, the evaluation criteria and grading method, the experimental setup and the test results discussion, and the gage capability analysis of the apparatus are presented. The new apparatus provides a method for the objective measurement and evaluation of the temperature regulating properties of thermal functional porous polymeric materials.

Non-equilibrium random matrix theory. Transition probabilities

International Nuclear Information System (INIS)

Pedro, Francisco Gil; Westphal, Alexander

2016-06-01

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

Non-equilibrium random matrix theory. Transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Pedro, Francisco Gil [Univ. Autonoma de Madrid (Spain). Dept. de Fisica Teorica; Westphal, Alexander [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Gruppe Theorie

2016-06-15

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

Loss-of-load probabilities for stand-alone photovoltaic systems

International Nuclear Information System (INIS)

Klein, S.A.; Beckman, W.A.

1989-01-01

A general method is presented for estimating the loss-of-load probability of stand-alone photovoltaic systems. The method was developed by correlating simulation results. The simulations were driven with synthetic radiation sequences having the same statistical significance as available historical data. The methods assumes a constant nighttime load and accounts for the distribution and persistence in daily solar radiation data. It is shown that the 10 year average performance of systems having loss-of-load probabilities less than about 0.01 can vary greatly from one ten year period to the next and thereby cannot be considered realistic performance estimates of a system during its lifetime. (author). 26 refs, 15 figs, 4 tabs

Probability theory versus simulation of petroleum potential in play analysis

Science.gov (United States)

Crovelli, R.A.

1987-01-01

An analytic probabilistic methodology for resource appraisal of undiscovered oil and gas resources in play analysis is presented. This play-analysis methodology is a geostochastic system for petroleum resource appraisal in explored as well as frontier areas. An objective was to replace an existing Monte Carlo simulation method in order to increase the efficiency of the appraisal process. Underlying the two methods is a single geologic model which considers both the uncertainty of the presence of the assessed hydrocarbon and its amount if present. The results of the model are resource estimates of crude oil, nonassociated gas, dissolved gas, and gas for a geologic play in terms of probability distributions. The analytic method is based upon conditional probability theory and a closed form solution of all means and standard deviations, along with the probabilities of occurrence. ?? 1987 J.C. Baltzer A.G., Scientific Publishing Company.

Reliability analysis of idealized tunnel support system using probability-based methods with case studies

Science.gov (United States)

Gharouni-Nik, Morteza; Naeimi, Meysam; Ahadi, Sodayf; Alimoradi, Zahra

2014-06-01

In order to determine the overall safety of a tunnel support lining, a reliability-based approach is presented in this paper. Support elements in jointed rock tunnels are provided to control the ground movement caused by stress redistribution during the tunnel drive. Main support elements contribute to stability of the tunnel structure are recognized owing to identify various aspects of reliability and sustainability in the system. The selection of efficient support methods for rock tunneling is a key factor in order to reduce the number of problems during construction and maintain the project cost and time within the limited budget and planned schedule. This paper introduces a smart approach by which decision-makers will be able to find the overall reliability of tunnel support system before selecting the final scheme of the lining system. Due to this research focus, engineering reliability which is a branch of statistics and probability is being appropriately applied to the field and much effort has been made to use it in tunneling while investigating the reliability of the lining support system for the tunnel structure. Therefore, reliability analysis for evaluating the tunnel support performance is the main idea used in this research. Decomposition approaches are used for producing system block diagram and determining the failure probability of the whole system. Effectiveness of the proposed reliability model of tunnel lining together with the recommended approaches is examined using several case studies and the final value of reliability obtained for different designing scenarios. Considering the idea of linear correlation between safety factors and reliability parameters, the values of isolated reliabilities determined for different structural components of tunnel support system. In order to determine individual safety factors, finite element modeling is employed for different structural subsystems and the results of numerical analyses are obtained in

Methods for estimating the probability of cancer from occupational radiation exposure

International Nuclear Information System (INIS)

1996-04-01

The aims of this TECDOC are to present the factors which are generally accepted as being responsible for cancer induction, to examine the role of radiation as a carcinogen, to demonstrate how the probability of cancer causation by radiation may be calculated and to inform the reader of the uncertainties that are associated with the use of various risk factors and models in such calculations. 139 refs, 2 tabs

Probability Sampling Method for a Hidden Population Using Respondent-Driven Sampling: Simulation for Cancer Survivors.

Science.gov (United States)

Jung, Minsoo

2015-01-01

When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.

Sizing of Compression Coil Springs Gas Regulators Using Modern Methods CAD and CAE

Directory of Open Access Journals (Sweden)

Adelin Ionel Tuţă

2010-10-01

Full Text Available This paper presents a method for compression coil springs sizing by gas regulators composition, using CAD techniques (Computer Aided Design and CAE (Computer Aided Engineering. Sizing is to optimize the functioning of the regulators under dynamic industrial and house-hold. Gas regulator is a device that automatically and continuously adjusted to maintain pre-set limits on output gas pressure at varying flow and input pressure. The performances of the pressure regulators like automatic systems depend on their behaviour under dynamic opera-tion. Time constant optimization of pneumatic actuators, which drives gas regulators, leads to a better functioning under their dynamic.

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....

Calculating the Probability of Returning a Loan with Binary Probability Models

Directory of Open Access Journals (Sweden)

Julian Vasilev

2014-12-01

Full Text Available The purpose of this article is to give a new approach in calculating the probability of returning a loan. A lot of factors affect the value of the probability. In this article by using statistical and econometric models some influencing factors are proved. The main approach is concerned with applying probit and logit models in loan management institutions. A new aspect of the credit risk analysis is given. Calculating the probability of returning a loan is a difficult task. We assume that specific data fields concerning the contract (month of signing, year of signing, given sum and data fields concerning the borrower of the loan (month of birth, year of birth (age, gender, region, where he/she lives may be independent variables in a binary logistics model with a dependent variable “the probability of returning a loan”. It is proved that the month of signing a contract, the year of signing a contract, the gender and the age of the loan owner do not affect the probability of returning a loan. It is proved that the probability of returning a loan depends on the sum of contract, the remoteness of the loan owner and the month of birth. The probability of returning a loan increases with the increase of the given sum, decreases with the proximity of the customer, increases for people born in the beginning of the year and decreases for people born at the end of the year.

Predicting the probability of slip in gait: methodology and distribution study.

Science.gov (United States)

Gragg, Jared; Yang, James

2016-01-01

The likelihood of a slip is related to the available and required friction for a certain activity, here gait. Classical slip and fall analysis presumed that a walking surface was safe if the difference between the mean available and required friction coefficients exceeded a certain threshold. Previous research was dedicated to reformulating the classical slip and fall theory to include the stochastic variation of the available and required friction when predicting the probability of slip in gait. However, when predicting the probability of a slip, previous researchers have either ignored the variation in the required friction or assumed the available and required friction to be normally distributed. Also, there are no published results that actually give the probability of slip for various combinations of required and available frictions. This study proposes a modification to the equation for predicting the probability of slip, reducing the previous equation from a double-integral to a more convenient single-integral form. Also, a simple numerical integration technique is provided to predict the probability of slip in gait: the trapezoidal method. The effect of the random variable distributions on the probability of slip is also studied. It is shown that both the required and available friction distributions cannot automatically be assumed as being normally distributed. The proposed methods allow for any combination of distributions for the available and required friction, and numerical results are compared to analytical solutions for an error analysis. The trapezoidal method is shown to be highly accurate and efficient. The probability of slip is also shown to be sensitive to the input distributions of the required and available friction. Lastly, a critical value for the probability of slip is proposed based on the number of steps taken by an average person in a single day.

Foundations of quantization for probability distributions

CERN Document Server

Graf, Siegfried

2000-01-01

Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.

Approximate solutions of the two-dimensional integral transport equation by collision probability methods

International Nuclear Information System (INIS)

Sanchez, Richard

1977-01-01

A set of approximate solutions for the isotropic two-dimensional neutron transport problem has been developed using the Interface Current formalism. The method has been applied to regular lattices of rectangular cells containing a fuel pin, cladding and water, or homogenized structural material. The cells are divided into zones which are homogeneous. A zone-wise flux expansion is used to formulate a direct collision probability problem within a cell. The coupling of the cells is made by making extra assumptions on the currents entering and leaving the interfaces. Two codes have been written: the first uses a cylindrical cell model and one or three terms for the flux expansion; the second uses a two-dimensional flux representation and does a truly two-dimensional calculation inside each cell. In both codes one or three terms can be used to make a space-independent expansion of the angular fluxes entering and leaving each side of the cell. The accuracies and computing times achieved with the different approximations are illustrated by numerical studies on two benchmark pr

Python for probability, statistics, and machine learning

CERN Document Server

Unpingco, José

2016-01-01

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...

Modeling highway travel time distribution with conditional probability models

Energy Technology Data Exchange (ETDEWEB)

Oliveira Neto, Francisco Moraes [ORNL; Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)

2014-01-01

ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

Science.gov (United States)

Crawford, Forrest W.; Suchard, Marc A.

2011-01-01

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with n current particles, a new particle is born with instantaneous rate λn and a particle dies with instantaneous rate μn. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics. PMID:21984359

Contributions to quantum probability

International Nuclear Information System (INIS)

Fritz, Tobias

2010-01-01

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome

The exact probability law for the approximated similarity from the ...

African Journals Online (AJOL)

The exact probability law for the approximated similarity from the Minhashing method. Soumaila Dembele, Gane Samb Lo. Abstract. We propose a probabilistic setting in which we study the probability law of the Rajaraman and Ullman RU algorithm and a modied version of it denoted by RUM. These algorithms aim at ...

Sensitivity analysis using probability bounding

International Nuclear Information System (INIS)

Ferson, Scott; Troy Tucker, W.

2006-01-01

Probability bounds analysis (PBA) provides analysts a convenient means to characterize the neighborhood of possible results that would be obtained from plausible alternative inputs in probabilistic calculations. We show the relationship between PBA and the methods of interval analysis and probabilistic uncertainty analysis from which it is jointly derived, and indicate how the method can be used to assess the quality of probabilistic models such as those developed in Monte Carlo simulations for risk analyses. We also illustrate how a sensitivity analysis can be conducted within a PBA by pinching inputs to precise distributions or real values

New results to BDD truncation method for efficient top event probability calculation

International Nuclear Information System (INIS)

Mo, Yuchang; Zhong, Farong; Zhao, Xiangfu; Yang, Quansheng; Cui, Gang

2012-01-01

A Binary Decision Diagram (BDD) is a graph-based data structure that calculates an exact top event probability (TEP). It has been a very difficult task to develop an efficient BDD algorithm that can solve a large problem since its memory consumption is very high. Recently, in order to solve a large reliability problem within limited computational resources, Jung presented an efficient method to maintain a small BDD size by a BDD truncation during a BDD calculation. In this paper, it is first identified that Jung's BDD truncation algorithm can be improved for a more practical use. Then, a more efficient truncation algorithm is proposed in this paper, which can generate truncated BDD with smaller size and approximate TEP with smaller truncation error. Empirical results showed this new algorithm uses slightly less running time and slightly more storage usage than Jung's algorithm. It was also found, that designing a truncation algorithm with ideal features for every possible fault tree is very difficult, if not impossible. The so-called ideal features of this paper would be that with the decrease of truncation limits, the size of truncated BDD converges to the size of exact BDD, but should never be larger than exact BDD.

Probability in physics

CERN Document Server

Hemmo, Meir

2012-01-01

What is the role and meaning of probability in physical theory, in particular in two of the most successful theories of our age, quantum physics and statistical mechanics? Laws once conceived as universal and deterministic, such as Newton‘s laws of motion, or the second law of thermodynamics, are replaced in these theories by inherently probabilistic laws. This collection of essays by some of the world‘s foremost experts presents an in-depth analysis of the meaning of probability in contemporary physics. Among the questions addressed are: How are probabilities defined? Are they objective or subjective? What is their  explanatory value? What are the differences between quantum and classical probabilities? The result is an informative and thought-provoking book for the scientifically inquisitive. 

Sequential Probability Ration Tests : Conservative and Robust

NARCIS (Netherlands)

Kleijnen, J.P.C.; Shi, Wen

2017-01-01

In practice, most computers generate simulation outputs sequentially, so it is attractive to analyze these outputs through sequential statistical methods such as sequential probability ratio tests (SPRTs). We investigate several SPRTs for choosing between two hypothesized values for the mean output

On estimating probability of presence from use-availability or presence-background data.

Science.gov (United States)

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

Dysphonic Voice Pattern Analysis of Patients in Parkinson’s Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods

Directory of Open Access Journals (Sweden)

Yunfeng Wu

2017-01-01

Full Text Available Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and related phonation disorders. In this paper, we first study the linear correlations between 22 voice parameters of fundamental frequency variability, amplitude variations, and nonlinear measures. The highly correlated vocal parameters are combined by using the linear discriminant analysis method. Based on the probability density functions estimated by the Parzen-window technique, we propose an interclass probability risk (ICPR method to select the vocal parameters with small ICPR values as dominant features and compare with the modified Kullback-Leibler divergence (MKLD feature selection approach. The experimental results show that the generalized logistic regression analysis (GLRA, support vector machine (SVM, and Bagging ensemble algorithm input with the ICPR features can provide better classification results than the same classifiers with the MKLD selected features. The SVM is much better at distinguishing normal vocal patterns with a specificity of 0.8542. Among the three classification methods, the Bagging ensemble algorithm with ICPR features can identify 90.77% vocal patterns, with the highest sensitivity of 0.9796 and largest area value of 0.9558 under the receiver operating characteristic curve. The classification results demonstrate the effectiveness of our feature selection and pattern analysis methods for dysphonic voice detection and measurement.

The Intersection Probability of Brownian Motion and SLEκ

Directory of Open Access Journals (Sweden)

Shizhong Zhou

2015-01-01

Full Text Available By using excursion measure Poisson kernel method, we obtain a second-order differential equation of the intersection probability of Brownian motion and SLEκ. Moreover, we find a transformation such that the second-order differential equation transforms into a hypergeometric differential equation. Then, by solving the hypergeometric differential equation, we obtain the explicit formula of the intersection probability for the trace of the chordal SLEκ and planar Brownian motion started from distinct points in an upper half-plane H-.

On the magnetization process and the associated probability in anisotropic cubic crystals

Energy Technology Data Exchange (ETDEWEB)

Khedr, D.M., E-mail: doaamohammed88@gmail.com [Department of Basic Science, Modern Academy of Engineering and Technology at Maadi, Cairo (Egypt); Aly, Samy H.; Shabara, Reham M. [Department of Physics, Faculty of Science at Damietta, University of Damietta, Damietta (Egypt); Yehia, Sherif [Department of Physics, Faculty of Science at Helwan, University of Helwan, Helwan (Egypt)

2017-05-15

We present a theoretical method to calculate specific magnetic properties, e.g. magnetization curves, magnetic susceptibility and probability landscapes along the [100], [110] and [111] crystallographic directions of a crystal of cubic symmetry. The probability landscape displays the evolution of the most probable angular orientation of the magnetization vector, for selected temperatures and magnetic fields. Our method is based on the premises of classical statistical mechanics. The energy density, used in the partition function, is the sum of magnetic anisotropy and Zeeman energies, however no other energies e.g. elastic or magnetoelastic terms are considered in the present work. Model cubic systems of diverse anisotropies are analyzed first, and subsequently material magnetic systems of cubic symmetry; namely iron, nickel and Co{sub x} Fe{sub 100−x} compounds, are discussed. We highlight a correlation between magnetization curves and the associated probability landscapes. In addition, determination of easiest axes of magnetization, using energy consideration, is done and compared with the results of the present method.

Probability based load combinations for design of category I structures

International Nuclear Information System (INIS)

Reich, M.; Hwang, H.

1985-01-01

This paper discusses a reliability analysis method and a procedure for developing the load combination design criteria for category I structures. For safety evaluation of category I concrete structures under various static and dynamic loads, a probability-based reliability analysis method has been developed. This reliability analysis method is also used as a tool for determining the load factors for design of category I structures. In this paper, the load combinations for design of concrete containments, corresponding to a target limit state probability of 1.0 x 10 -6 in 4 years, are described. A comparison of containments designed using the ASME code and the proposed design criteria is also presented

A dynamic model for firm-response to non-credible incentive regulation regimes

International Nuclear Information System (INIS)

Agrell, Per J.; Grifell-Tatjé, Emili

2016-01-01

Economic network regulation increasingly use quantitative performance models (from econometrics and engineering) to set revenues. In theory, high-powered incentive regulation, such as revenue-caps, induces firms to cost-efficient behavior independent of underlying model. However, anecdotal evidence shows regulated firms occasionally maintaining cost-inefficiency under incentive regulation even under slumping profitability. We present a model for firm-level efficiency under a regime with a probability of failure explaining this phenomenon. The model is based on the hypothesis that the regulatory choice of method can be associated with intrinsic flaws leading to judicial repeal and replacement of it by a low-powered regime. The results show that the cost efficiency policy is proportional to the type of firm (cost of effort), value of time (discount factor) and the credibility of the method (risk of failure). A panel data set for 2000–2006 for 128 electricity distributors in Sweden is used to validate the model predictions (radical productivity slowdown, failing profitability and efficiency) at the launch and demise of a non-credible regulation method. The work highlights the fallacy of viewing incentive regulation as a method-independent instrument, a result applicable in any infrastructure regulation. - Highlights: • Incentive regulation relies on fixed revenue for operators. • In existing theory the efficiency-inducing effect is model-independent. • A dynamic game exposes the firm to a regulation that may fail. • One optimal policy is to pad cost and wait for the failure. • The Swedish DSOs show this policy 2003–2006, when the regime failed.

Uncertainty the soul of modeling, probability & statistics

CERN Document Server

Briggs, William

2016-01-01

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...

Estimation of long-term probabilities for inadvertent intrusion into radioactive waste management areas

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

Control Surface Fault Diagnosis with Specified Detection Probability - Real Event Experiences

DEFF Research Database (Denmark)

Hansen, Søren; Blanke, Mogens

2013-01-01

desired levels of false alarms and detection probabilities. Self-tuning residual generators are employed for diagnosis and are combined with statistical change detection to form a setup for robust fault diagnosis. On-line estimation of test statistics is used to obtain a detection threshold and a desired...... false alarm probability. A data based method is used to determine the validity of the methods proposed. Verification is achieved using real data and shows that the presented diagnosis method is efficient and could have avoided incidents where faults led to loss of aircraft....

Large deviations and idempotent probability

CERN Document Server

Puhalskii, Anatolii

2001-01-01

In the view of many probabilists, author Anatolii Puhalskii''s research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the connections between the large deviation principle (LDP) and well-known methods for establishing weak convergence results.Large Deviations and Idempotent Probability expounds upon the recent methodology of building large deviation theory along the lines of weak convergence theory. The author develops an idempotent (or maxitive) probability theory, introduces idempotent analogues of martingales (maxingales), Wiener and Poisson processes, and Ito differential equations, and studies their properties. The large deviation principle for stochastic processes is formulated as a certain type of convergence of stochastic processes to idempotent processes. The author calls this large deviation convergence.The approach to establishing large deviation convergence uses novel com...

Men who have sex with men in Great Britain: comparing methods and estimates from probability and convenience sample surveys

OpenAIRE

Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H

2016-01-01

Objective: To examine sociodemographic and behavioural differences between men whohave sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey.\\ud Methods: We compared 148 MSM aged 18–64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010–2012, with men inthe same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European...

Philosophical theories of probability

CERN Document Server

Gillies, Donald

2000-01-01

The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. Philosophical Theories of Probability is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.

Volume regulation in epithelia

DEFF Research Database (Denmark)

Larsen, Erik Hviid; Hoffmann, Else Kay

2016-01-01

to amphibian skin and mammalian cortical collecting tubule of low and intermediate osmotic permeability. Crosstalk between entrance and exit mechanisms interferes with volume regulation both at aniso-osmotic and iso-osmotic volume perturbations. It has been proposed that cell volume regulation is an intrinsic...... regulation are cloned. The volume-regulated anion channel (VRAC) exhibiting specific electrophysiological characteristics seems exclusive to serve cell volume regulation. This is contrary to K+ channels as well as cotransporters and exchange mechanisms that may serve both transepithelial transport and cell...... volume regulation. In the same cell, these functions may be maintained by different ion pathways that are separately regulated. RVD is often preceded by increase in cytosolic free Ca2+, probably via influx through TRP channels, but Ca2+ release from intracellular stores has also been observed. Cell...

Probability and information theory, with applications to radar

CERN Document Server

Woodward, P M; Higinbotham, W

1964-01-01

Electronics and Instrumentation, Second Edition, Volume 3: Probability and Information Theory with Applications to Radar provides information pertinent to the development on research carried out in electronics and applied physics. This book presents the established mathematical techniques that provide the code in which so much of the mathematical theory of electronics and radar is expressed.Organized into eight chapters, this edition begins with an overview of the geometry of probability distributions in which moments play a significant role. This text then examines the mathematical methods in

Contributions to quantum probability

Energy Technology Data Exchange (ETDEWEB)

Fritz, Tobias

2010-06-25

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

International Nuclear Information System (INIS)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

2013-01-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

Science.gov (United States)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

2013-03-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

Estimating reliability of degraded system based on the probability density evolution with multi-parameter

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.

The distributed failure probability approach to dependent failure analysis, and its application

International Nuclear Information System (INIS)

Hughes, R.P.

1989-01-01

The Distributed Failure Probability (DFP) approach to the problem of dependent failures in systems is presented. The basis of the approach is that the failure probability of a component is a variable. The source of this variability is the change in the 'environment' of the component, where the term 'environment' is used to mean not only obvious environmental factors such as temperature etc., but also such factors as the quality of maintenance and manufacture. The failure probability is distributed among these various 'environments' giving rise to the Distributed Failure Probability method. Within the framework which this method represents, modelling assumptions can be made, based both on engineering judgment and on the data directly. As such, this DFP approach provides a soundly based and scrutable technique by which dependent failures can be quantitatively assessed. (orig.)

A brief introduction to probability.

Science.gov (United States)

Di Paola, Gioacchino; Bertani, Alessandro; De Monte, Lavinia; Tuzzolino, Fabio

2018-02-01

The theory of probability has been debated for centuries: back in 1600, French mathematics used the rules of probability to place and win bets. Subsequently, the knowledge of probability has significantly evolved and is now an essential tool for statistics. In this paper, the basic theoretical principles of probability will be reviewed, with the aim of facilitating the comprehension of statistical inference. After a brief general introduction on probability, we will review the concept of the "probability distribution" that is a function providing the probabilities of occurrence of different possible outcomes of a categorical or continuous variable. Specific attention will be focused on normal distribution that is the most relevant distribution applied to statistical analysis.

Real analysis and probability

CERN Document Server

Ash, Robert B; Lukacs, E

1972-01-01

Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory.Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of var

Probability and Measure

CERN Document Server

Billingsley, Patrick

2012-01-01

Praise for the Third Edition "It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006) A complete and comprehensive classic in probability and measure theory Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this

Experimental Probability in Elementary School

Science.gov (United States)

Andrew, Lane

2009-01-01

Concepts in probability can be more readily understood if students are first exposed to probability via experiment. Performing probability experiments encourages students to develop understandings of probability grounded in real events, as opposed to merely computing answers based on formulae.

Pointwise probability reinforcements for robust statistical inference.

Science.gov (United States)

Frénay, Benoît; Verleysen, Michel

2014-02-01

Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Risk-based methods for reliability investments in electric power distribution systems

Energy Technology Data Exchange (ETDEWEB)

Alvehag, Karin

2011-07-01

Society relies more and more on a continuous supply of electricity. However, while under investments in reliability lead to an unacceptable number of power interruptions, over investments result in too high costs for society. To give incentives for a socio economically optimal level of reliability, quality regulations have been adopted in many European countries. These quality regulations imply new financial risks for the distribution system operator (DSO) since poor reliability can reduce the allowed revenue for the DSO and compensation may have to be paid to affected customers. This thesis develops a method for evaluating the incentives for reliability investments implied by different quality regulation designs. The method can be used to investigate whether socio economically beneficial projects are also beneficial for a profit-maximizing DSO subject to a particular quality regulation design. To investigate which reinvestment projects are preferable for society and a DSO, risk-based methods are developed. With these methods, the probability of power interruptions and the consequences of these can be simulated. The consequences of interruptions for the DSO will to a large extent depend on the quality regulation. The consequences for the customers, and hence also society, will depend on factors such as the interruption duration and time of occurrence. The proposed risk-based methods consider extreme outage events in the risk assessments by incorporating the impact of severe weather, estimating the full probability distribution of the total reliability cost, and formulating a risk-averse strategy. Results from case studies performed show that quality regulation design has a significant impact on reinvestment project profitability for a DSO. In order to adequately capture the financial risk that the DSO is exposed to, detailed riskbased methods, such as the ones developed in this thesis, are needed. Furthermore, when making investment decisions, a risk

Probability measures, Lévy measures and analyticity in time

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Hubalek, Friedrich

2008-01-01

We investigate the relation of the semigroup probability density of an infinite activity Lévy process to the corresponding Lévy density. For subordinators, we provide three methods to compute the former from the latter. The first method is based on approximating compound Poisson distributions...

Probability Measures, Lévy Measures, and Analyticity in Time

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Hubalek, Friedrich

We investigate the relation of the semigroup probability density of an infinite activity Lévy process to the corresponding Lévy density. For subordinators we provide three methods to compute the former from the latter. The first method is based on approximating compound Poisson distributions...

Probabilities in physics

CERN Document Server

Hartmann, Stephan

2011-01-01

Many results of modern physics--those of quantum mechanics, for instance--come in a probabilistic guise. But what do probabilistic statements in physics mean? Are probabilities matters of objective fact and part of the furniture of the world, as objectivists think? Or do they only express ignorance or belief, as Bayesians suggest? And how are probabilistic hypotheses justified and supported by empirical evidence? Finally, what does the probabilistic nature of physics imply for our understanding of the world? This volume is the first to provide a philosophical appraisal of probabilities in all of physics. Its main aim is to make sense of probabilistic statements as they occur in the various physical theories and models and to provide a plausible epistemology and metaphysics of probabilities. The essays collected here consider statistical physics, probabilistic modelling, and quantum mechanics, and critically assess the merits and disadvantages of objectivist and subjectivist views of probabilities in these fie...

Probability an introduction

CERN Document Server

Grimmett, Geoffrey

2014-01-01

Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains. A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures. The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford. The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit th...

Evaluation of nuclear power plant component failure probability and core damage probability using simplified PSA model

International Nuclear Information System (INIS)

Shimada, Yoshio

2000-01-01

It is anticipated that the change of frequency of surveillance tests, preventive maintenance or parts replacement of safety related components may cause the change of component failure probability and result in the change of core damage probability. It is also anticipated that the change is different depending on the initiating event frequency or the component types. This study assessed the change of core damage probability using simplified PSA model capable of calculating core damage probability in a short time period, which is developed by the US NRC to process accident sequence precursors, when various component's failure probability is changed between 0 and 1, or Japanese or American initiating event frequency data are used. As a result of the analysis, (1) It was clarified that frequency of surveillance test, preventive maintenance or parts replacement of motor driven pumps (high pressure injection pumps, residual heat removal pumps, auxiliary feedwater pumps) should be carefully changed, since the core damage probability's change is large, when the base failure probability changes toward increasing direction. (2) Core damage probability change is insensitive to surveillance test frequency change, since the core damage probability change is small, when motor operated valves and turbine driven auxiliary feed water pump failure probability changes around one figure. (3) Core damage probability change is small, when Japanese failure probability data are applied to emergency diesel generator, even if failure probability changes one figure from the base value. On the other hand, when American failure probability data is applied, core damage probability increase is large, even if failure probability changes toward increasing direction. Therefore, when Japanese failure probability data is applied, core damage probability change is insensitive to surveillance tests frequency change etc. (author)

Probability biases as Bayesian inference

Directory of Open Access Journals (Sweden)

Andre; C. R. Martins

2006-11-01

Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.

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

Generation, combination and extension of random set approximations to coherent lower and upper probabilities

International Nuclear Information System (INIS)

Hall, Jim W.; Lawry, Jonathan

2004-01-01

Random set theory provides a convenient mechanism for representing uncertain knowledge including probabilistic and set-based information, and extending it through a function. This paper focuses upon the situation when the available information is in terms of coherent lower and upper probabilities, which are encountered, for example, when a probability distribution is specified by interval parameters. We propose an Iterative Rescaling Method (IRM) for constructing a random set with corresponding belief and plausibility measures that are a close outer approximation to the lower and upper probabilities. The approach is compared with the discrete approximation method of Williamson and Downs (sometimes referred to as the p-box), which generates a closer approximation to lower and upper cumulative probability distributions but in most cases a less accurate approximation to the lower and upper probabilities on the remainder of the power set. Four combination methods are compared by application to example random sets generated using the IRM

76 FR 5319 - Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline

Science.gov (United States)

2011-01-31

... Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline AGENCY: Environmental... gasoline. This proposed rule will provide flexibility to the regulated community by allowing an additional... A. Alternative Test Method for Olefins in Gasoline III. Statutory and Executive Order Reviews A...

76 FR 65382 - Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline

Science.gov (United States)

2011-10-21

... Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline AGENCY: Environmental... gasoline. This final rule will provide flexibility to the regulated community by allowing an additional... Method for Olefins in Gasoline III. Statutory and Executive Order Reviews A. Executive Order 12866...

Probability dynamics of a repopulating tumor in case of fractionated external radiotherapy.

Science.gov (United States)

Stavreva, Nadia; Stavrev, Pavel; Fallone, B Gino

2009-12-01

In this work two analytical methods are developed for computing the probability distribution of the number of surviving cells of a repopulating tumor during a fractionated external radio-treatment. Both methods are developed for the case of pure birth processes. They both allow the description of the tumor dynamics in case of cell radiosensitivity changing in time and for treatment schedules with variable dose per fraction and variable time intervals between fractions. The first method is based on a direct solution of the set of differential equations describing the tumor dynamics. The second method is based on the works of Hanin et al. [Hanin LG, Zaider M, Yakovlev AY. Distribution of the number of clonogens surviving fractionated radiotherapy: a long-standing problem revisited. Int J Radiat Biol 2001;77:205-13; Hanin LG. Iterated birth and death process as a model of radiation cell survival. Math Biosci 2001;169:89-107; Hanin LG. A stochastic model of tumor response to fractionated radiation: limit theorems and rate of convergence. Math Biosci 2004;191:1-17], where probability generating functions are used. In addition a Monte Carlo algorithm for simulating the probability distributions is developed for the same treatment conditions as for the analytical methods. The probability distributions predicted by the three methods are compared graphically for a certain set of values of the model parameters and an excellent agreement is found to exist between all three results, thus proving the correct implementation of the methods. However, numerical difficulties have been encountered with both analytical methods depending on the values of the model parameters. Therefore, the Poisson approximation is also studied and it is compared to the exact methods for several different combinations of the model parameter values. It is concluded that the Poisson approximation works sufficiently well only for slowly repopulating tumors and a low cell survival probability and that it

A method for regulating strong nonlinear vibration energy of the flexible arm

Directory of Open Access Journals (Sweden)

Yushu Bian

2015-07-01

Full Text Available For an oscillating system, large amplitude indicates strong vibration energy. In this article, modal interaction is used as a useful means to regulate strong nonlinear vibration energy of the flexible arm undergoing rigid motion. A method is put forward to migrate and dissipate vibration energy based on modal interaction. By means of multiple-scale perturbation analysis, it is proven that internal resonance can be successfully established between modes of the flexible arm and the vibration absorber. Through examples and analyses, it is verified that this control method is effective in regulating strong vibration energy and can be used to suppress strong nonlinear vibration of the flexible arm undergoing rigid motion.

Introduction to probability

CERN Document Server

Freund, John E

1993-01-01

Thorough, lucid coverage of permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, binomial distribution, geometric distribution, standard deviation, law of large numbers, and much more. Exercises with some solutions. Summary. Bibliography. Includes 42 black-and-white illustrations. 1973 edition.

A new plan-scoring method using normal tissue complication probability for personalized treatment plan decisions in prostate cancer

Science.gov (United States)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie; Chang, Kyung Hwan

2018-01-01

The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group ( n = 7) and a similar group ( n = 12), using treatment plan verification software that we developed. The quality factor ( QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.

Modulation Based on Probability Density Functions

Science.gov (United States)

Williams, Glenn L.

2009-01-01

A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.

An analytical evaluation for spatial-dependent intra-pebble Dancoff factor and escape probability

International Nuclear Information System (INIS)

Kim, Songhyun; Kim, Hong-Chul; Kim, Jong Kyung; Kim, Soon Young; Noh, Jae Man

2009-01-01

The analytical evaluation of spatial-dependent intra-pebble Dancoff factors and their escape probabilities is pursued by the model developed in this study. Intra-pebble Dancoff factors and their escape probabilities are calculated as a function of fuel kernel radius, number of fuel kernels, and fuel region radius. The method in this study can be easily utilized to analyze the tendency of spatial-dependent intra-pebble Dancoff factor and spatial-dependent fuel region escape probability for the various geometries because it is faster than the MCNP method as well as good accuracy. (author)

Calendar methods of fertility regulation: a rule of thumb.

Science.gov (United States)

Colombo, B; Scarpa, B

1996-01-01

"[Many] illiterate women, particularly in the third world, find [it] difficult to apply usual calendar methods for the regulation of fertility. Some of them are even unable to make simple subtractions. In this paper we are therefore trying to evaluate the applicability and the efficiency of an extremely simple rule which entails only [the ability to count] a number of days, and always the same way." (SUMMARY IN ITA) excerpt

Numerical determination of transmission probabilities in cylindrical geometry

International Nuclear Information System (INIS)

Queiroz Bogado Leite, S. de.

1989-11-01

Efficient methods for numerical calculation of transmission probabilities in cylindrical geometry are presented. Relative errors of the order of 10 -5 or smaller are obtained using analytical solutions and low order quadrature integration schemes. (author) [pt

Probably not future prediction using probability and statistical inference

CERN Document Server

Dworsky, Lawrence N

2008-01-01

An engaging, entertaining, and informative introduction to probability and prediction in our everyday lives Although Probably Not deals with probability and statistics, it is not heavily mathematical and is not filled with complex derivations, proofs, and theoretical problem sets. This book unveils the world of statistics through questions such as what is known based upon the information at hand and what can be expected to happen. While learning essential concepts including "the confidence factor" and "random walks," readers will be entertained and intrigued as they move from chapter to chapter. Moreover, the author provides a foundation of basic principles to guide decision making in almost all facets of life including playing games, developing winning business strategies, and managing personal finances. Much of the book is organized around easy-to-follow examples that address common, everyday issues such as: How travel time is affected by congestion, driving speed, and traffic lights Why different gambling ...

A three-step Maximum-A-Posterior probability method for InSAR data inversion of coseismic rupture with application to four recent large earthquakes in Asia

Science.gov (United States)

Sun, J.; Shen, Z.; Burgmann, R.; Liang, F.

2012-12-01

We develop a three-step Maximum-A-Posterior probability (MAP) method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic solutions of earthquake rupture. The method originates from the Fully Bayesian Inversion (FBI) and the Mixed linear-nonlinear Bayesian inversion (MBI) methods , shares the same a posterior PDF with them and keeps most of their merits, while overcoming its convergence difficulty when large numbers of low quality data are used and improving the convergence rate greatly using optimization procedures. A highly efficient global optimization algorithm, Adaptive Simulated Annealing (ASA), is used to search for the maximum posterior probability in the first step. The non-slip parameters are determined by the global optimization method, and the slip parameters are inverted for using the least squares method without positivity constraint initially, and then damped to physically reasonable range. This step MAP inversion brings the inversion close to 'true' solution quickly and jumps over local maximum regions in high-dimensional parameter space. The second step inversion approaches the 'true' solution further with positivity constraints subsequently applied on slip parameters using the Monte Carlo Inversion (MCI) technique, with all parameters obtained from step one as the initial solution. Then the slip artifacts are eliminated from slip models in the third step MAP inversion with fault geometry parameters fixed. We first used a designed model with 45 degree dipping angle and oblique slip, and corresponding synthetic InSAR data sets to validate the efficiency and accuracy of method. We then applied the method on four recent large earthquakes in Asia, namely the 2010 Yushu, China earthquake, the 2011 Burma earthquake, the 2011 New Zealand earthquake and the 2008 Qinghai, China earthquake, and compared our results with those results from other groups. Our results show the effectiveness of

Risk Probabilities

DEFF Research Database (Denmark)

Rojas-Nandayapa, Leonardo

Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...

Traffic simulation based ship collision probability modeling

Energy Technology Data Exchange (ETDEWEB)

Goerlandt, Floris, E-mail: floris.goerlandt@tkk.f [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland); Kujala, Pentti [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland)

2011-01-15

Maritime traffic poses various risks in terms of human, environmental and economic loss. In a risk analysis of ship collisions, it is important to get a reasonable estimate for the probability of such accidents and the consequences they lead to. In this paper, a method is proposed to assess the probability of vessels colliding with each other. The method is capable of determining the expected number of accidents, the locations where and the time when they are most likely to occur, while providing input for models concerned with the expected consequences. At the basis of the collision detection algorithm lays an extensive time domain micro-simulation of vessel traffic in the given area. The Monte Carlo simulation technique is applied to obtain a meaningful prediction of the relevant factors of the collision events. Data obtained through the Automatic Identification System is analyzed in detail to obtain realistic input data for the traffic simulation: traffic routes, the number of vessels on each route, the ship departure times, main dimensions and sailing speed. The results obtained by the proposed method for the studied case of the Gulf of Finland are presented, showing reasonable agreement with registered accident and near-miss data.

Evaluation of burst probability for tubes by Weibull distributions

International Nuclear Information System (INIS)

Kao, S.

1975-10-01

The investigations of candidate distributions that best describe the burst pressure failure probability characteristics of nuclear power steam generator tubes has been continued. To date it has been found that the Weibull distribution provides an acceptable fit for the available data from both the statistical and physical viewpoints. The reasons for the acceptability of the Weibull distribution are stated together with the results of tests for the suitability of fit. In exploring the acceptability of the Weibull distribution for the fitting, a graphical method to be called the ''density-gram'' is employed instead of the usual histogram. With this method a more sensible graphical observation on the empirical density may be made for cases where the available data is very limited. Based on these methods estimates of failure pressure are made for the left-tail probabilities

To Measure Probable Physical Changes On The Earth During Total Solar Eclipse Using Geophysical Methods

International Nuclear Information System (INIS)

Gocmen, C.

2007-01-01

When the total solar eclipse came into question, people connected the eclipse with the earthquake dated 17.08.1999. We thought if any physical parameters change during total solar eclipse on the earth, we could measure this changing and we did the project 'To Measure Probable Physical Changes On The Earth During Total Solar Eclipse Using Geophysical Methods' We did gravity, magnetic and self-potential measurements at Konya and Ankara during total solar eclipse (29, March, 2006) and the day before eclipse and the day after eclipse. The measurements went on three days continuously twenty-four hours at Konya and daytime in Ankara. Bogazici University Kandilli Observatory gave us magnetic values in Istanbul and we compare the values with our magnetic values. Turkish State Meteorological Service sent us temperature and air pressure observations during three days, in Konya and Ankara. We interpreted all of them

Quantum Zeno and anti-Zeno effects measured by transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wenxian, E-mail: wxzhang@whu.edu.cn [School of Physics and Technology, Wuhan University, Wuhan, Hubei 430072 (China); Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Kavli Institute for Theoretical Physics China, CAS, Beijing 100190 (China); Kofman, A.G. [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States); Zhuang, Jun [Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); You, J.Q. [Beijing Computational Science Research Center, Beijing 10084 (China); Department of Physics, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Nori, Franco [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States)

2013-10-30

Using numerical calculations, we compare the transition probabilities of many spins in random magnetic fields, subject to either frequent projective measurements, frequent phase modulations, or a mix of modulations and measurements. For various distribution functions, we find the transition probability under frequent modulations is suppressed most if the pulse delay is short and the evolution time is larger than a critical value. Furthermore, decay freezing occurs only under frequent modulations as the pulse delay approaches zero. In the large pulse-delay region, however, the transition probabilities under frequent modulations are highest among the three control methods.

Mixed analytical-stochastic simulation method for the recovery of a Brownian gradient source from probability fluxes to small windows.

Science.gov (United States)

Dobramysl, U; Holcman, D

2018-02-15

Is it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical procedure to avoid tracking Brownian trajectories in the entire infinite space. Instead, we generate particles near the absorbing windows, computed from the analytical expression of the exit probability. When the Brownian particles are generated by a steady-state gradient at a single point, we compute asymptotically the fluxes to small absorbing holes distributed on the boundary of half-space and on a disk in two dimensions, which agree with stochastic simulations. We also derive an expression for the splitting probability between small windows using the matched asymptotic method. Finally, when there are more than two small absorbing windows, we show how to reconstruct the position of the source from the diffusion fluxes. The present approach provides a computational first principle for the mechanism of sensing a gradient of diffusing particles, a ubiquitous problem in cell biology.

Quantum processes: probability fluxes, transition probabilities in unit time and vacuum vibrations

International Nuclear Information System (INIS)

Oleinik, V.P.; Arepjev, Ju D.

1989-01-01

Transition probabilities in unit time and probability fluxes are compared in studying the elementary quantum processes -the decay of a bound state under the action of time-varying and constant electric fields. It is shown that the difference between these quantities may be considerable, and so the use of transition probabilities W instead of probability fluxes Π, in calculating the particle fluxes, may lead to serious errors. The quantity W represents the rate of change with time of the population of the energy levels relating partly to the real states and partly to the virtual ones, and it cannot be directly measured in experiment. The vacuum background is shown to be continuously distorted when a perturbation acts on a system. Because of this the viewpoint of an observer on the physical properties of real particles continuously varies with time. This fact is not taken into consideration in the conventional theory of quantum transitions based on using the notion of probability amplitude. As a result, the probability amplitudes lose their physical meaning. All the physical information on quantum dynamics of a system is contained in the mean values of physical quantities. The existence of considerable differences between the quantities W and Π permits one in principle to make a choice of the correct theory of quantum transitions on the basis of experimental data. (author)

USING THE WEB-SERVICES WOLFRAM|ALPHA TO SOLVE PROBLEMS IN PROBABILITY THEORY

Directory of Open Access Journals (Sweden)

Taras Kobylnyk

2015-10-01

Full Text Available The trend towards the use of remote network resources on the Internet clearly delineated. Traditional training combined with increasingly networked, remote technologies become popular cloud computing. Research methods of probability theory are used in various fields. Of particular note is the use of methods of probability theory in psychological and educational research in statistical analysis of experimental data. Conducting such research is impossible without the use of modern information technology. Given the advantages of web-based software, the article describes web-service Wolfram|Alpha. Detailed analysis of the possibilities of using web-service Wolfram|Alpha for solving problems of probability theory. In the case studies described the results of queries for solving of probability theory, in particular the sections random events and random variables. Considered and analyzed the problem of the number of occurrences of event A in n independent trials using Wolfram|Alpha, detailed analysis of the possibilities of using the service Wolfram|Alpha for the study of continuous random variable that has a normal and uniform probability distribution, including calculating the probability of getting the value of a random variable in a given interval. The problem in applying the binomial and hypergeometric probability distribution of a discrete random variable and demonstrates the possibility of using the service Wolfram|Alpha for solving it.

Sequential probability ratio controllers for safeguards radiation monitors

International Nuclear Information System (INIS)

Fehlau, P.E.; Coop, K.L.; Nixon, K.V.

1984-01-01

Sequential hypothesis tests applied to nuclear safeguards accounting methods make the methods more sensitive to detecting diversion. The sequential tests also improve transient signal detection in safeguards radiation monitors. This paper describes three microprocessor control units with sequential probability-ratio tests for detecting transient increases in radiation intensity. The control units are designed for three specific applications: low-intensity monitoring with Poisson probability ratios, higher intensity gamma-ray monitoring where fixed counting intervals are shortened by sequential testing, and monitoring moving traffic where the sequential technique responds to variable-duration signals. The fixed-interval controller shortens a customary 50-s monitoring time to an average of 18 s, making the monitoring delay less bothersome. The controller for monitoring moving vehicles benefits from the sequential technique by maintaining more than half its sensitivity when the normal passage speed doubles

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.

Limited test data: The choice between confidence limits and inverse probability

International Nuclear Information System (INIS)

Nichols, P.

1975-01-01

For a unit which has been successfully designed to a high standard of reliability, any test programme of reasonable size will result in only a small number of failures. In these circumstances the failure rate estimated from the tests will depend on the statistical treatment applied. When a large number of units is to be manufactured, an unexpected high failure rate will certainly result in a large number of failures, so it is necessary to guard against optimistic unrepresentative test results by using a confidence limit approach. If only a small number of production units is involved, failures may not occur even with a higher than expected failure rate, and so one may be able to accept a method which allows for the possibility of either optimistic or pessimistic test results, and in this case an inverse probability approach, based on Bayes' theorem, might be used. The paper first draws attention to an apparently significant difference in the numerical results from the two methods, particularly for the overall probability of several units arranged in redundant logic. It then discusses a possible objection to the inverse method, followed by a demonstration that, for a large population and a very reasonable choice of prior probability, the inverse probability and confidence limit methods give the same numerical result. Finally, it is argued that a confidence limit approach is overpessimistic when a small number of production units is involved, and that both methods give the same answer for a large population. (author)

Feynman quasi probability distribution for spin-(1/2), and its generalizations

International Nuclear Information System (INIS)

Colucci, M.

1999-01-01

It has been examined the Feynman's paper Negative probability, in which, after a discussion about the possibility of attributing a real physical meaning to quasi probability distributions, he introduces a new kind of distribution for spin-(1/2), with a possible method of generalization to systems with arbitrary number of states. The principal aim of this article is to shed light upon the method of construction of these distributions, taking into consideration their application to some experiments, and discussing their positive and negative aspects

Upregulation of transmitter release probability improves a conversion of synaptic analogue signals into neuronal digital spikes

Science.gov (United States)

2012-01-01

Action potentials at the neurons and graded signals at the synapses are primary codes in the brain. In terms of their functional interaction, the studies were focused on the influence of presynaptic spike patterns on synaptic activities. How the synapse dynamics quantitatively regulates the encoding of postsynaptic digital spikes remains unclear. We investigated this question at unitary glutamatergic synapses on cortical GABAergic neurons, especially the quantitative influences of release probability on synapse dynamics and neuronal encoding. Glutamate release probability and synaptic strength are proportionally upregulated by presynaptic sequential spikes. The upregulation of release probability and the efficiency of probability-driven synaptic facilitation are strengthened by elevating presynaptic spike frequency and Ca2+. The upregulation of release probability improves spike capacity and timing precision at postsynaptic neuron. These results suggest that the upregulation of presynaptic glutamate release facilitates a conversion of synaptic analogue signals into digital spikes in postsynaptic neurons, i.e., a functional compatibility between presynaptic and postsynaptic partners. PMID:22852823

Propensity, Probability, and Quantum Theory

Science.gov (United States)

Ballentine, Leslie E.

2016-08-01

Quantum mechanics and probability theory share one peculiarity. Both have well established mathematical formalisms, yet both are subject to controversy about the meaning and interpretation of their basic concepts. Since probability plays a fundamental role in QM, the conceptual problems of one theory can affect the other. We first classify the interpretations of probability into three major classes: (a) inferential probability, (b) ensemble probability, and (c) propensity. Class (a) is the basis of inductive logic; (b) deals with the frequencies of events in repeatable experiments; (c) describes a form of causality that is weaker than determinism. An important, but neglected, paper by P. Humphreys demonstrated that propensity must differ mathematically, as well as conceptually, from probability, but he did not develop a theory of propensity. Such a theory is developed in this paper. Propensity theory shares many, but not all, of the axioms of probability theory. As a consequence, propensity supports the Law of Large Numbers from probability theory, but does not support Bayes theorem. Although there are particular problems within QM to which any of the classes of probability may be applied, it is argued that the intrinsic quantum probabilities (calculated from a state vector or density matrix) are most naturally interpreted as quantum propensities. This does not alter the familiar statistical interpretation of QM. But the interpretation of quantum states as representing knowledge is untenable. Examples show that a density matrix fails to represent knowledge.

Bayesian noninferiority test for 2 binomial probabilities as the extension of Fisher exact test.

Science.gov (United States)

Doi, Masaaki; Takahashi, Fumihiro; Kawasaki, Yohei

2017-12-30

Noninferiority trials have recently gained importance for the clinical trials of drugs and medical devices. In these trials, most statistical methods have been used from a frequentist perspective, and historical data have been used only for the specification of the noninferiority margin Δ>0. In contrast, Bayesian methods, which have been studied recently are advantageous in that they can use historical data to specify prior distributions and are expected to enable more efficient decision making than frequentist methods by borrowing information from historical trials. In the case of noninferiority trials for response probabilities π 1 ,π 2 , Bayesian methods evaluate the posterior probability of H 1 :π 1 >π 2 -Δ being true. To numerically calculate such posterior probability, complicated Appell hypergeometric function or approximation methods are used. Further, the theoretical relationship between Bayesian and frequentist methods is unclear. In this work, we give the exact expression of the posterior probability of the noninferiority under some mild conditions and propose the Bayesian noninferiority test framework which can flexibly incorporate historical data by using the conditional power prior. Further, we show the relationship between Bayesian posterior probability and the P value of the Fisher exact test. From this relationship, our method can be interpreted as the Bayesian noninferior extension of the Fisher exact test, and we can treat superiority and noninferiority in the same framework. Our method is illustrated through Monte Carlo simulations to evaluate the operating characteristics, the application to the real HIV clinical trial data, and the sample size calculation using historical data. Copyright © 2017 John Wiley & Sons, Ltd.

Probability intervals for the top event unavailability of fault trees

International Nuclear Information System (INIS)

Lee, Y.T.; Apostolakis, G.E.

1976-06-01

The evaluation of probabilities of rare events is of major importance in the quantitative assessment of the risk from large technological systems. In particular, for nuclear power plants the complexity of the systems, their high reliability and the lack of significant statistical records have led to the extensive use of logic diagrams in the estimation of low probabilities. The estimation of probability intervals for the probability of existence of the top event of a fault tree is examined. Given the uncertainties of the primary input data, a method is described for the evaluation of the first four moments of the top event occurrence probability. These moments are then used to estimate confidence bounds by several approaches which are based on standard inequalities (e.g., Tchebycheff, Cantelli, etc.) or on empirical distributions (the Johnson family). Several examples indicate that the Johnson family of distributions yields results which are in good agreement with those produced by Monte Carlo simulation

Methods for ensuring compliance with regulatory requirements: regulators and operators

International Nuclear Information System (INIS)

Fleischmann, A.W.

1989-01-01

Some of the methods of ensuring compliance with regulatory requirements contained in various radiation protection documents such as Regulations, ICRP Recommendations etc. are considered. These include radiation safety officers and radiation safety committees, personnel monitoring services, dissemination of information, inspection services and legislative power of enforcement. Difficulties in ensuring compliance include outmoded legislation, financial and personnel constraints

Birth/birth-death processes and their computable transition probabilities with biological applications.

Science.gov (United States)

Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2018-03-01

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

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

The extinction probability in systems randomly varying in time

Directory of Open Access Journals (Sweden)

Imre Pázsit

2017-09-01

Full Text Available The extinction probability of a branching process (a neutron chain in a multiplying medium is calculated for a system randomly varying in time. The evolution of the first two moments of such a process was calculated previously by the authors in a system randomly shifting between two states of different multiplication properties. The same model is used here for the investigation of the extinction probability. It is seen that the determination of the extinction probability is significantly more complicated than that of the moments, and it can only be achieved by pure numerical methods. The numerical results indicate that for systems fluctuating between two subcritical or two supercritical states, the extinction probability behaves as expected, but for systems fluctuating between a supercritical and a subcritical state, there is a crucial and unexpected deviation from the predicted behaviour. The results bear some significance not only for neutron chains in a multiplying medium, but also for the evolution of biological populations in a time-varying environment.

Prediction and probability in sciences

International Nuclear Information System (INIS)

Klein, E.; Sacquin, Y.

1998-01-01

This book reports the 7 presentations made at the third meeting 'physics and fundamental questions' whose theme was probability and prediction. The concept of probability that was invented to apprehend random phenomena has become an important branch of mathematics and its application range spreads from radioactivity to species evolution via cosmology or the management of very weak risks. The notion of probability is the basis of quantum mechanics and then is bound to the very nature of matter. The 7 topics are: - radioactivity and probability, - statistical and quantum fluctuations, - quantum mechanics as a generalized probability theory, - probability and the irrational efficiency of mathematics, - can we foresee the future of the universe?, - chance, eventuality and necessity in biology, - how to manage weak risks? (A.C.)

Count data, detection probabilities, and the demography, dynamics, distribution, and decline of amphibians.

Science.gov (United States)

Schmidt, Benedikt R

2003-08-01

The evidence for amphibian population declines is based on count data that were not adjusted for detection probabilities. Such data are not reliable even when collected using standard methods. The formula C = Np (where C is a count, N the true parameter value, and p is a detection probability) relates count data to demography, population size, or distributions. With unadjusted count data, one assumes a linear relationship between C and N and that p is constant. These assumptions are unlikely to be met in studies of amphibian populations. Amphibian population data should be based on methods that account for detection probabilities.

A Multidisciplinary Approach for Teaching Statistics and Probability

Science.gov (United States)

Rao, C. Radhakrishna

1971-01-01

The author presents a syllabus for an introductory (first year after high school) course in statistics and probability and some methods of teaching statistical techniques. The description comes basically from the procedures used at the Indian Statistical Institute, Calcutta. (JG)

Heart sounds analysis using probability assessment.

Science.gov (United States)

Plesinger, F; Viscor, I; Halamek, J; Jurco, J; Jurak, P

2017-07-31

This paper describes a method for automated discrimination of heart sounds recordings according to the Physionet Challenge 2016. The goal was to decide if the recording refers to normal or abnormal heart sounds or if it is not possible to decide (i.e. 'unsure' recordings). Heart sounds S1 and S2 are detected using amplitude envelopes in the band 15-90 Hz. The averaged shape of the S1/S2 pair is computed from amplitude envelopes in five different bands (15-90 Hz; 55-150 Hz; 100-250 Hz; 200-450 Hz; 400-800 Hz). A total of 53 features are extracted from the data. The largest group of features is extracted from the statistical properties of the averaged shapes; other features are extracted from the symmetry of averaged shapes, and the last group of features is independent of S1 and S2 detection. Generated features are processed using logical rules and probability assessment, a prototype of a new machine-learning method. The method was trained using 3155 records and tested on 1277 hidden records. It resulted in a training score of 0.903 (sensitivity 0.869, specificity 0.937) and a testing score of 0.841 (sensitivity 0.770, specificity 0.913). The revised method led to a test score of 0.853 in the follow-up phase of the challenge. The presented solution achieved 7th place out of 48 competing entries in the Physionet Challenge 2016 (official phase). In addition, the PROBAfind software for probability assessment was introduced.

Environmental regulations and plant exit: A logit analysis based on established panel data

Energy Technology Data Exchange (ETDEWEB)

Bioern, E; Golombek, R; Raknerud, A

1995-12-01

This publication uses a model to study the relationship between environmental regulations and plant exit. It has the main characteristics of a multinomial qualitative response model of the logit type, but also has elements of a Markov chain model. The model uses Norwegian panel data for establishments in three manufacturing sectors with high shares of units which have been under strict environmental regulations. In two of the sectors, the exit probability of non-regulated establishments is about three times higher than for regulated ones. It is also found that the probability of changing regulation status from non-regulated to regulated depends significantly on economic factors. In particular, establishments with weak profitability are the most likely to become subject to environmental regulation. 12 refs., 2 figs., 6 tabs.

Decomposition of conditional probability for high-order symbolic Markov chains

Science.gov (United States)

Melnik, S. S.; Usatenko, O. V.

2017-07-01

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements. At weak correlations, the memory functions are uniquely expressed in terms of the high-order symbolic correlation functions. The proposed method fills the gap between two approaches, namely the likelihood estimation and the additive Markov chains. The obtained results may have applications for sequential approximation of artificial neural network training.

Bayesian Analysis for EMP Survival Probability of Solid State Relay

International Nuclear Information System (INIS)

Sun Beiyun; Zhou Hui; Cheng Xiangyue; Mao Congguang

2009-01-01

The principle to estimate the parameter p of binomial distribution by Bayesian method and the several non-informative prior are introduced. The survival probability of DC solid state relay under current injection at certain amplitude is obtained by this method. (authors)

Evolvement simulation of the probability of neutron-initiating persistent fission chain

International Nuclear Information System (INIS)

Wang Zhe; Hong Zhenying

2014-01-01

Background: Probability of neutron-initiating persistent fission chain, which has to be calculated in analysis of critical safety, start-up of reactor, burst waiting time on pulse reactor, bursting time on pulse reactor, etc., is an inherent parameter in a multiplying assembly. Purpose: We aim to derive time-dependent integro-differential equation for such probability in relative velocity space according to the probability conservation, and develop the deterministic code Dynamic Segment Number Probability (DSNP) based on the multi-group S N method. Methods: The reliable convergence of dynamic calculation was analyzed and numerical simulation of the evolvement process of dynamic probability for varying concentration was performed under different initial conditions. Results: On Highly Enriched Uranium (HEU) Bare Spheres, when the time is long enough, the results of dynamic calculation approach to those of static calculation. The most difference of such results between DSNP and Partisn code is less than 2%. On Baker model, over the range of about 1 μs after the first criticality, the most difference between the dynamic and static calculation is about 300%. As for a super critical system, the finite fission chains decrease and the persistent fission chains increase as the reactivity aggrandizes, the dynamic evolvement curve of initiation probability is close to the static curve within the difference of 5% when the K eff is more than 1.2. The cumulative probability curve also indicates that the difference of integral results between the dynamic calculation and the static calculation decreases from 35% to 5% as the K eff increases. This demonstrated that the ability of initiating a self-sustaining fission chain reaction approaches stabilization, while the former difference (35%) showed the important difference of the dynamic results near the first criticality with the static ones. The DSNP code agrees well with Partisn code. Conclusions: There are large numbers of

Assessing the Probability that a Finding Is Genuine for Large-Scale Genetic Association Studies.

Science.gov (United States)

Kuo, Chia-Ling; Vsevolozhskaya, Olga A; Zaykin, Dmitri V

2015-01-01

Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity of P-values and the automated way they are, as a rule, produced by software packages. Attempts to design simple ways to convert an association P-value into the probability that a finding is spurious have been met with difficulties. The False Positive Report Probability (FPRP) method has gained increasing popularity. However, FPRP is not designed to estimate the probability for a particular finding, because it is defined for an entire region of hypothetical findings with P-values at least as small as the one observed for that finding. Here we propose a method that lets researchers extract probability that a finding is spurious directly from a P-value. Considering the counterpart of that probability, we term this method POFIG: the Probability that a Finding is Genuine. Our approach shares FPRP's simplicity, but gives a valid probability that a finding is spurious given a P-value. In addition to straightforward interpretation, POFIG has desirable statistical properties. The POFIG average across a set of tentative associations provides an estimated proportion of false discoveries in that set. POFIGs are easily combined across studies and are immune to multiple testing and selection bias. We illustrate an application of POFIG method via analysis of GWAS associations with Crohn's disease.

The quantum probability calculus

International Nuclear Information System (INIS)

Jauch, J.M.

1976-01-01

The Wigner anomaly (1932) for the joint distribution of noncompatible observables is an indication that the classical probability calculus is not applicable for quantum probabilities. It should, therefore, be replaced by another, more general calculus, which is specifically adapted to quantal systems. In this article this calculus is exhibited and its mathematical axioms and the definitions of the basic concepts such as probability field, random variable, and expectation values are given. (B.R.H)

Dynamic phase transitions of the Blume–Emery–Griffiths model under an oscillating external magnetic field by the path probability method

Energy Technology Data Exchange (ETDEWEB)

Ertaş, Mehmet, E-mail: mehmetertas@erciyes.edu.tr; Keskin, Mustafa

2015-03-01

By using the path probability method (PPM) with point distribution, we study the dynamic phase transitions (DPTs) in the Blume–Emery–Griffiths (BEG) model under an oscillating external magnetic field. The phases in the model are obtained by solving the dynamic equations for the average order parameters and a disordered phase, ordered phase and four mixed phases are found. We also investigate the thermal behavior of the dynamic order parameters to analyze the nature dynamic transitions as well as to obtain the DPT temperatures. The dynamic phase diagrams are presented in three different planes in which exhibit the dynamic tricritical point, double critical end point, critical end point, quadrupole point, triple point as well as the reentrant behavior, strongly depending on the values of the system parameters. We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory. - Highlights: • Dynamic magnetic behavior of the Blume–Emery–Griffiths system is investigated by using the path probability method. • The time variations of average magnetizations are studied to find the phases. • The temperature dependence of the dynamic magnetizations is investigated to obtain the dynamic phase transition points. • We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory.

Dynamic phase transitions of the Blume–Emery–Griffiths model under an oscillating external magnetic field by the path probability method

International Nuclear Information System (INIS)

Ertaş, Mehmet; Keskin, Mustafa

2015-01-01

By using the path probability method (PPM) with point distribution, we study the dynamic phase transitions (DPTs) in the Blume–Emery–Griffiths (BEG) model under an oscillating external magnetic field. The phases in the model are obtained by solving the dynamic equations for the average order parameters and a disordered phase, ordered phase and four mixed phases are found. We also investigate the thermal behavior of the dynamic order parameters to analyze the nature dynamic transitions as well as to obtain the DPT temperatures. The dynamic phase diagrams are presented in three different planes in which exhibit the dynamic tricritical point, double critical end point, critical end point, quadrupole point, triple point as well as the reentrant behavior, strongly depending on the values of the system parameters. We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory. - Highlights: • Dynamic magnetic behavior of the Blume–Emery–Griffiths system is investigated by using the path probability method. • The time variations of average magnetizations are studied to find the phases. • The temperature dependence of the dynamic magnetizations is investigated to obtain the dynamic phase transition points. • We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory

Space Object Collision Probability via Monte Carlo on the Graphics Processing Unit

Science.gov (United States)

Vittaldev, Vivek; Russell, Ryan P.

2017-09-01

Fast and accurate collision probability computations are essential for protecting space assets. Monte Carlo (MC) simulation is the most accurate but computationally intensive method. A Graphics Processing Unit (GPU) is used to parallelize the computation and reduce the overall runtime. Using MC techniques to compute the collision probability is common in literature as the benchmark. An optimized implementation on the GPU, however, is a challenging problem and is the main focus of the current work. The MC simulation takes samples from the uncertainty distributions of the Resident Space Objects (RSOs) at any time during a time window of interest and outputs the separations at closest approach. Therefore, any uncertainty propagation method may be used and the collision probability is automatically computed as a function of RSO collision radii. Integration using a fixed time step and a quartic interpolation after every Runge Kutta step ensures that no close approaches are missed. Two orders of magnitude speedups over a serial CPU implementation are shown, and speedups improve moderately with higher fidelity dynamics. The tool makes the MC approach tractable on a single workstation, and can be used as a final product, or for verifying surrogate and analytical collision probability methods.

'PRIZE': A program for calculating collision probabilities in R-Z geometry

International Nuclear Information System (INIS)

Pitcher, H.H.W.

1964-10-01

PRIZE is an IBM7090 program which computes collision probabilities for systems with axial symmetry and outputs them on cards in suitable format for the PIP1 program. Its method of working, data requirements, output, running time and accuracy are described. The program has been used to compute non-escape (self-collision) probabilities of finite circular cylinders, and a table is given by which non-escape probabilities of slabs, finite and infinite circular cylinders, infinite square cylinders, cubes, spheres and hemispheres may quickly be calculated to 1/2% or better. (author)

Excluding joint probabilities from quantum theory

Science.gov (United States)

Allahverdyan, Armen E.; Danageozian, Arshag

2018-03-01

Quantum theory does not provide a unique definition for the joint probability of two noncommuting observables, which is the next important question after the Born's probability for a single observable. Instead, various definitions were suggested, e.g., via quasiprobabilities or via hidden-variable theories. After reviewing open issues of the joint probability, we relate it to quantum imprecise probabilities, which are noncontextual and are consistent with all constraints expected from a quantum probability. We study two noncommuting observables in a two-dimensional Hilbert space and show that there is no precise joint probability that applies for any quantum state and is consistent with imprecise probabilities. This contrasts with theorems by Bell and Kochen-Specker that exclude joint probabilities for more than two noncommuting observables, in Hilbert space with dimension larger than two. If measurement contexts are included into the definition, joint probabilities are not excluded anymore, but they are still constrained by imprecise probabilities.

HELIOS: transformation laws for multiple-collision probabilities with angular dependence

International Nuclear Information System (INIS)

Villarino, E.A.; Stamm'ler, R.J.J.

1996-01-01

In the lattice code HELIOS, neutron and gamma transport in a given system is treated by the CCCP (current-coupling collision-probability) method. The system is partitioned into space elements which are coupled by currents. Inside the space elements first-flight probabilities are used to obtain the coefficients of the coupling equation and of the equations for the fluxes. The calculation of these coefficients is expensive in CPU time on two scores: the evaluation of the first-flight probabilities, and the matrix inversion to convert these probabilities into the desired coefficients. If the cross sections of two geometrically equal space elements, or of the same element at an earlier burnup level, differ less than a small fraction, considerable CPU time can be saved by using transformation laws. Previously, such laws were derived for first-flight probabilities; here, they are derived for the multiple-collision coefficients of the CCCP equations. They avoid not only the expensive calculations of the first-flight probabilities, but also the subsequent matrix inversion. Various examples illustrate the savings achieved by using these new transformation laws - or by directly using earlier calculated coefficients, if the cross section differences are negligible. (author)

Probability and statistics in particle physics

International Nuclear Information System (INIS)

Frodesen, A.G.; Skjeggestad, O.

1979-01-01

Probability theory is entered into at an elementary level and given a simple and detailed exposition. The material on statistics has been organised with an eye to the experimental physicist's practical need, which is likely to be statistical methods for estimation or decision-making. The book is intended for graduate students and research workers in experimental high energy and elementary particle physics, and numerous examples from these fields are presented. (JIW)

Linear positivity and virtual probability

International Nuclear Information System (INIS)

Hartle, James B.

2004-01-01

We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics

The pleasures of probability

CERN Document Server

Isaac, Richard

1995-01-01

The ideas of probability are all around us. Lotteries, casino gambling, the al­ most non-stop polling which seems to mold public policy more and more­ these are a few of the areas where principles of probability impinge in a direct way on the lives and fortunes of the general public. At a more re­ moved level there is modern science which uses probability and its offshoots like statistics and the theory of random processes to build mathematical descriptions of the real world. In fact, twentieth-century physics, in embrac­ ing quantum mechanics, has a world view that is at its core probabilistic in nature, contrary to the deterministic one of classical physics. In addition to all this muscular evidence of the importance of probability ideas it should also be said that probability can be lots of fun. It is a subject where you can start thinking about amusing, interesting, and often difficult problems with very little mathematical background. In this book, I wanted to introduce a reader with at least a fairl...

Probable Inference and Quantum Mechanics

International Nuclear Information System (INIS)

Grandy, W. T. Jr.

2009-01-01

In its current very successful interpretation the quantum theory is fundamentally statistical in nature. Although commonly viewed as a probability amplitude whose (complex) square is a probability, the wavefunction or state vector continues to defy consensus as to its exact meaning, primarily because it is not a physical observable. Rather than approach this problem directly, it is suggested that it is first necessary to clarify the precise role of probability theory in quantum mechanics, either as applied to, or as an intrinsic part of the quantum theory. When all is said and done the unsurprising conclusion is that quantum mechanics does not constitute a logic and probability unto itself, but adheres to the long-established rules of classical probability theory while providing a means within itself for calculating the relevant probabilities. In addition, the wavefunction is seen to be a description of the quantum state assigned by an observer based on definite information, such that the same state must be assigned by any other observer based on the same information, in much the same way that probabilities are assigned.

Wald Sequential Probability Ratio Test for Space Object Conjunction Assessment

Science.gov (United States)

Carpenter, James R.; Markley, F Landis

2014-01-01

This paper shows how satellite owner/operators may use sequential estimates of collision probability, along with a prior assessment of the base risk of collision, in a compound hypothesis ratio test to inform decisions concerning collision risk mitigation maneuvers. The compound hypothesis test reduces to a simple probability ratio test, which appears to be a novel result. The test satisfies tolerances related to targeted false alarm and missed detection rates. This result is independent of the method one uses to compute the probability density that one integrates to compute collision probability. A well-established test case from the literature shows that this test yields acceptable results within the constraints of a typical operational conjunction assessment decision timeline. Another example illustrates the use of the test in a practical conjunction assessment scenario based on operations of the International Space Station.

Psychophysics of the probability weighting function

Science.gov (United States)

Takahashi, Taiki

2011-03-01

A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(-() (01e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec's probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.

Probability concepts in quality risk management.

Science.gov (United States)

Claycamp, H Gregg

2012-01-01

Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although risk is generally a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management tools are relatively silent on the meaning and uses of "probability." The probability concept is typically applied by risk managers as a combination of frequency-based calculation and a "degree of belief" meaning of probability. Probability as a concept that is crucial for understanding and managing risk is discussed through examples from the most general, scenario-defining and ranking tools that use probability implicitly to more specific probabilistic tools in risk management. A rich history of probability in risk management applied to other fields suggests that high-quality risk management decisions benefit from the implementation of more thoughtful probability concepts in both risk modeling and risk management. Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although "risk" generally describes a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management methodologies and respective tools focus on managing severity but are relatively silent on the in-depth meaning and uses of "probability." Pharmaceutical manufacturers are expanding their use of quality risk management to identify and manage risks to the patient that might occur in phases of the pharmaceutical life cycle from drug development to manufacture, marketing to product discontinuation. A probability concept is typically applied by risk managers as a combination of data-based measures of probability and a subjective "degree of belief" meaning of probability. Probability as

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

Science.gov (United States)

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

The perception of probability.

Science.gov (United States)

Gallistel, C R; Krishan, Monika; Liu, Ye; Miller, Reilly; Latham, Peter E

2014-01-01

We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Probabilities for gravitational lensing by point masses in a locally inhomogeneous universe

International Nuclear Information System (INIS)

Isaacson, J.A.; Canizares, C.R.

1989-01-01

Probability functions for gravitational lensing by point masses that incorporate Poisson statistics and flux conservation are formulated in the Dyer-Roeder construction. Optical depths to lensing for distant sources are calculated using both the method of Press and Gunn (1973) which counts lenses in an otherwise empty cone, and the method of Ehlers and Schneider (1986) which projects lensing cross sections onto the source sphere. These are then used as parameters of the probability density for lensing in the case of a critical (q0 = 1/2) Friedmann universe. A comparison of the probability functions indicates that the effects of angle-averaging can be well approximated by adjusting the average magnification along a random line of sight so as to conserve flux. 17 references

Calculating failure probabilities for TRISO-coated fuel particles using an integral formulation

International Nuclear Information System (INIS)

Miller, Gregory K.; Maki, John T.; Knudson, Darrell L.; Petti, David A.

2010-01-01

The fundamental design for a gas-cooled reactor relies on the safe behavior of the coated particle fuel. The coating layers surrounding the fuel kernels in these spherical particles, termed the TRISO coating, act as a pressure vessel that retains fission products. The quality of the fuel is reflected in the number of particle failures that occur during reactor operation, where failed particles become a source for fission products that can then diffuse through the fuel element. The failure probability for any batch of particles, which has traditionally been calculated using the Monte Carlo method, depends on statistical variations in design parameters and on variations in the strengths of coating layers among particles in the batch. An alternative approach to calculating failure probabilities is developed herein that uses direct numerical integration of a failure probability integral. Because this is a multiple integral where the statistically varying parameters become integration variables, a fast numerical integration approach is also developed. In sample cases analyzed involving multiple failure mechanisms, results from the integration methods agree closely with Monte Carlo results. Additionally, the fast integration approach, particularly, is shown to significantly improve efficiency of failure probability calculations. These integration methods have been implemented in the PARFUME fuel performance code along with the Monte Carlo method, where each serves to verify accuracy of the others.

Survival probability of diffusion with trapping in cellular neurobiology

Science.gov (United States)

Holcman, David; Marchewka, Avi; Schuss, Zeev

2005-09-01

The problem of diffusion with absorption and trapping sites arises in the theory of molecular signaling inside and on the membranes of biological cells. In particular, this problem arises in the case of spine-dendrite communication, where the number of calcium ions, modeled as random particles, is regulated across the spine microstructure by pumps, which play the role of killing sites, while the end of the dendritic shaft is an absorbing boundary. We develop a general mathematical framework for diffusion in the presence of absorption and killing sites and apply it to the computation of the time-dependent survival probability of ions. We also compute the ratio of the number of absorbed particles at a specific location to the number of killed particles. We show that the ratio depends on the distribution of killing sites. The biological consequence is that the position of the pumps regulates the fraction of calcium ions that reach the dendrite.

PROCOPE, Collision Probability in Pin Clusters and Infinite Rod Lattices

International Nuclear Information System (INIS)

Amyot, L.; Daolio, C.; Benoist, P.

1984-01-01

1 - Nature of physical problem solved: Calculation of directional collision probabilities in pin clusters and infinite rod lattices. 2 - Method of solution: a) Gauss integration of analytical expressions for collision probabilities. b) alternately, an approximate closed expression (not involving integrals) may be used for pin-to-pin interactions. 3 - Restrictions on the complexity of the problem: number of fuel pins must be smaller than 62; maximum number of groups of symmetry is 300

Reliability assessment and probability based design of reinforced concrete containments and shear walls

International Nuclear Information System (INIS)

Hwang, H.; Reich, M.; Ellingwood, B.; Shinozuka, M.

1986-03-01

This report summarizes work completed under the program entitled, ''Probability-Based Load Combinations for Design of Category I Structures.'' Under this program, the probabilistic models for various static and dynamic loads were formulated. The randomness and uncertainties in material strengths and structural resistance were established. Several limit states of concrete containments and shear walls were identified and analytically formulated. Furthermore, the reliability analysis methods for estimating limit state probabilities were established. These reliability analysis methods can be used to evaluate the safety levels of nuclear structures under various combinations of static and dynamic loads. They can also be used to generate analytically the fragility data for PRA studies. In addition to the development of reliability analysis methods, probability-based design criteria for concrete containments and shear wall structures have also been developed. The proposed design criteria are in the load and resistance factor design (LRFD) format. The load and resistance factors are determined for several limit states and target limit state probabilities. Thus, the proposed design criteria are risk-consistent and have a well-established rationale. 73 refs., 18 figs., 16 tabs

Do natural methods for fertility regulation increase the risks of genetic errors?

Science.gov (United States)

Serra, A

1981-09-01

Genetic errors of many kinds are connected with the reproductive processes and are favored by a nunber of largely uncontrollable, endogenous, and/or exogenous factors. For a long time human beings have taken into their own hands the control of this process. The regulation of fertility is clearly a forceful request to any family, to any community, were it only to lower the level of the consequences of genetic errors. In connection with this request, and in the context of the Congress for the Family of Africa and Europe (Catholic University, January 1981), 1 question must still be raised and possibly answered. The question is: do or can the so called "natural methods" for the regulation of fertility increase the risks of genetic errors with their generally dramatic effects on families and on communities. It is important to try to give as far as possible a scientifically based answer to this question. Fr. Haring, a moral theologian, citing scientific evidence finds it shocking that the rhythm method, so strongly and recently endorsed again by Church authorities, should be classified among the means of "birth control" by way of spontaneous abortion or at least by spontaneous loss of a large number of zygotes which, due to the concrete application of the rhythm method, lack of necessary vitality for survival. He goes on to state that the scientific research provides overwhelming evidence that the rhythm method in its traditional form is responsible for a disproportionate waste of zygotes and a disproportionate frequency of spontaneous abortions and a defective childern. Professor Hilgers, a reproductive physiologist, takes on opposite view, maintaining that the hypotheses are arbitrary and the alarm false. The strongest evidence upon which Fr. Haring bases his moral principles about the use of the natural methods of fertility regulation is a paper by Guerrero and Rojos (1975). These authors examined, retrospectively, the success of 965 pregnancies which occurred in

Κ-electron capture probability in 167Tm

International Nuclear Information System (INIS)

Sree Krishna Murty, G.; Chandrasekhar Rao, M.V.S.; Radha Krishna, K.; Bhuloka Reddy, S.; Satyanarayana, G.; Ramana Rao, P.V.; Sastry, D.L.

1990-01-01

The Κ-electron capture probability in the decay of 167 Tm for the first-forbidden transition 1/2 + →3/2 - was measured using the sum-coincidence method and employing a hyper-pure Ge system. The P Κ value is found to be 0.835±0.029, in agreement with the theoretical value of 0.829. (author)

Quantification of the probable effects of alternative in-river harvest regulations on recovery of Snake River fall chinook salmon. Final report

International Nuclear Information System (INIS)

Cramer, S.P.; Vigg, S.

1996-03-01

The goal of this study was to quantify the probable effects that alternative strategies for managing in-river harvest would have on recovery of Snake River fall chinook salmon. This report presents the analysis of existing data to quantify the way in which various in-river harvest strategies catch Snake River bright (SRB) fall chinook. Because there has been disagreement among experts regarding the magnitude of in-river harvest impacts on Snake River fall chinook, the authors compared the results from using the following three different methods to estimate in-river harvest rates: (1) use of run reconstruction through stock accounting of escapement and landings data to estimate harvest rate of SRB chinook in Zone 6 alone; (2) use of Coded Wire Tag (CWT) recoveries of fall chinook from Lyons Ferry Hatchery in a cohort analysis to estimate age and sex specific harvest rates for Zone 6 and for below Bonneville Dam; (3) comparison of harvest rates estimated for SRB chinook by the above methods to those estimated by the same methods for Upriver Bright (URB) fall chinook

Introduction to probability with R

CERN Document Server

Baclawski, Kenneth

2008-01-01

FOREWORD PREFACE Sets, Events, and Probability The Algebra of Sets The Bernoulli Sample Space The Algebra of Multisets The Concept of Probability Properties of Probability Measures Independent Events The Bernoulli Process The R Language Finite Processes The Basic Models Counting Rules Computing Factorials The Second Rule of Counting Computing Probabilities Discrete Random Variables The Bernoulli Process: Tossing a Coin The Bernoulli Process: Random Walk Independence and Joint Distributions Expectations The Inclusion-Exclusion Principle General Random Variable

Most probable dimension value and most flat interval methods for automatic estimation of dimension from time series

International Nuclear Information System (INIS)

Corana, A.; Bortolan, G.; Casaleggio, A.

2004-01-01

We present and compare two automatic methods for dimension estimation from time series. Both methods, based on conceptually different approaches, work on the derivative of the bi-logarithmic plot of the correlation integral versus the correlation length (log-log plot). The first method searches for the most probable dimension values (MPDV) and associates to each of them a possible scaling region. The second one searches for the most flat intervals (MFI) in the derivative of the log-log plot. The automatic procedures include the evaluation of the candidate scaling regions using two reliability indices. The data set used to test the methods consists of time series from known model attractors with and without the addition of noise, structured time series, and electrocardiographic signals from the MIT-BIH ECG database. Statistical analysis of results was carried out by means of paired t-test, and no statistically significant differences were found in the large majority of the trials. Consistent results are also obtained dealing with 'difficult' time series. In general for a more robust and reliable estimate, the use of both methods may represent a good solution when time series from complex systems are analyzed. Although we present results for the correlation dimension only, the procedures can also be used for the automatic estimation of generalized q-order dimensions and pointwise dimension. We think that the proposed methods, eliminating the need of operator intervention, allow a faster and more objective analysis, thus improving the usefulness of dimension analysis for the characterization of time series obtained from complex dynamical systems

Series-parallel method of direct solar array regulation

Science.gov (United States)

Gooder, S. T.

1976-01-01

A 40 watt experimental solar array was directly regulated by shorting out appropriate combinations of series and parallel segments of a solar array. Regulation switches were employed to control the array at various set-point voltages between 25 and 40 volts. Regulation to within + or - 0.5 volt was obtained over a range of solar array temperatures and illumination levels as an active load was varied from open circuit to maximum available power. A fourfold reduction in regulation switch power dissipation was achieved with series-parallel regulation as compared to the usual series-only switching for direct solar array regulation.

A new hydraulic regulation method on district heating system with distributed variable-speed pumps

International Nuclear Information System (INIS)

Wang, Hai; Wang, Haiying; Zhu, Tong

2017-01-01

Highlights: • A hydraulic regulation method was presented for district heating with distributed variable speed pumps. • Information and automation technologies were utilized to support the proposed method. • A new hydraulic model was developed for distributed variable speed pumps. • A new optimization model was developed based on genetic algorithm. • Two scenarios of a multi-source looped system was illustrated to validate the method. - Abstract: Compared with the hydraulic configuration based on the conventional central circulating pump, a district heating system with distributed variable-speed-pumps configuration can often save 30–50% power consumption on circulating pumps with frequency inverters. However, the hydraulic regulations on distributed variable-speed-pumps configuration could be more complicated than ever while all distributed pumps need to be adjusted to their designated flow rates. Especially in a multi-source looped structure heating network where the distributed pumps have strongly coupled and severe non-linear hydraulic connections with each other, it would be rather difficult to maintain the hydraulic balance during the regulations. In this paper, with the help of the advanced automation and information technologies, a new hydraulic regulation method was proposed to achieve on-site hydraulic balance for the district heating systems with distributed variable-speed-pumps configuration. The proposed method was comprised of a new hydraulic model, which was developed to adapt the distributed variable-speed-pumps configuration, and a calibration model with genetic algorithm. By carrying out the proposed method step by step, the flow rates of all distributed pumps can be progressively adjusted to their designated values. A hypothetic district heating system with 2 heat sources and 10 substations was taken as a case study to illustrate the feasibility of the proposed method. Two scenarios were investigated respectively. In Scenario I, the

The second iteration of the Systems Prioritization Method: A systems prioritization and decision-aiding tool for the Waste Isolation Pilot Plant: Volume 1, Synopsis of method and results

International Nuclear Information System (INIS)

Prindle, N.H.; Mendenhall, F.T.; Boak, D.M.

1996-05-01

In March 1994, the US Department of Energy Carlsbad Area Office (DOE/CAO) embarked on an effort to design and implement a performance- based decision-aiding tool to provide an analytical basis for planning, prioritizing, and selecting programmatic options for the Waste Isolation Pilot Plant (WIPP). This tool, called Systems Prioritization Method (SPM) defines the most viable combinations of scientific investigations, engineered alternatives (EAs), and waste acceptance criteria (WAC) for supporting the final WIPP compliance application. The scope of SPM is restricted to selected portions of applicable Environmental Protection Agency (EPA) long-term performance regulations. SPM calculates the probabilities of certain sets of activities demonstrating compliance with various regulations. SPM provides results in the form of a decision matrix to identify cost-effective programmatic paths with a high probability of successfully demonstrating compliance

The second iteration of the Systems Prioritization Method: A systems prioritization and decision-aiding tool for the Waste Isolation Pilot Plant: Volume 1, Synopsis of method and results

Energy Technology Data Exchange (ETDEWEB)

Prindle, N.H.; Mendenhall, F.T.; Boak, D.M. [and others

1996-05-01

In March 1994, the US Department of Energy Carlsbad Area Office (DOE/CAO) embarked on an effort to design and implement a performance- based decision-aiding tool to provide an analytical basis for planning, prioritizing, and selecting programmatic options for the Waste Isolation Pilot Plant (WIPP). This tool, called Systems Prioritization Method (SPM) defines the most viable combinations of scientific investigations, engineered alternatives (EAs), and waste acceptance criteria (WAC) for supporting the final WIPP compliance application. The scope of SPM is restricted to selected portions of applicable Environmental Protection Agency (EPA) long-term performance regulations. SPM calculates the probabilities of certain sets of activities demonstrating compliance with various regulations. SPM provides results in the form of a decision matrix to identify cost-effective programmatic paths with a high probability of successfully demonstrating compliance.

134Cs emission probabilities determination by gamma spectrometry

Science.gov (United States)

de Almeida, M. C. M.; Poledna, R.; Delgado, J. U.; Silva, R. L.; Araujo, M. T. F.; da Silva, C. J.

2018-03-01

The National Laboratory for Ionizing Radiation Metrology (LNMRI/IRD/CNEN) of Rio de Janeiro performed primary and secondary standardization of different radionuclides reaching satisfactory uncertainties. A solution of 134Cs radionuclide was purchased from commercial supplier to emission probabilities determination of some of its energies. 134Cs is a beta gamma emitter with 754 days of half-life. This radionuclide is used as standard in environmental, water and food control. It is also important to germanium detector calibration. The gamma emission probabilities (Pγ) were determined mainly for some energies of the 134Cs by efficiency curve method and the Pγ absolute uncertainties obtained were below 1% (k=1).

Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

Science.gov (United States)

Frahm, Klaus M.; Shepelyansky, Dima L.

2014-04-01

We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

Determining the nucleation rate from the dimer growth probability

NARCIS (Netherlands)

Ter Horst, J.H.; Kashchiev, D.

2005-01-01

A new method is proposed for the determination of the stationary one-component nucleation rate J with the help of data for the growth probability P2 of a dimer which is the smallest cluster of the nucleating phase. The method is based on an exact formula relating J and P2, and is readily applicable

Smoothing and projecting age-specific probabilities of death by TOPALS

Directory of Open Access Journals (Sweden)

Joop de Beer

2012-10-01

Full Text Available BACKGROUND TOPALS is a new relational model for smoothing and projecting age schedules. The model is operationally simple, flexible, and transparent. OBJECTIVE This article demonstrates how TOPALS can be used for both smoothing and projecting age-specific mortality for 26 European countries and compares the results of TOPALS with those of other smoothing and projection methods. METHODS TOPALS uses a linear spline to describe the ratios between the age-specific death probabilities of a given country and a standard age schedule. For smoothing purposes I use the average of death probabilities over 15 Western European countries as standard, whereas for projection purposes I use an age schedule of 'best practice' mortality. A partial adjustment model projects how quickly the death probabilities move in the direction of the best-practice level of mortality. RESULTS On average, TOPALS performs better than the Heligman-Pollard model and the Brass relational method in smoothing mortality age schedules. TOPALS can produce projections that are similar to those of the Lee-Carter method, but can easily be used to produce alternative scenarios as well. This article presents three projections of life expectancy at birth for the year 2060 for 26 European countries. The Baseline scenario assumes a continuation of the past trend in each country, the Convergence scenario assumes that there is a common trend across European countries, and the Acceleration scenario assumes that the future decline of death probabilities will exceed that in the past. The Baseline scenario projects that average European life expectancy at birth will increase to 80 years for men and 87 years for women in 2060, whereas the Acceleration scenario projects an increase to 90 and 93 years respectively. CONCLUSIONS TOPALS is a useful new tool for demographers for both smoothing age schedules and making scenarios.

Probability density function method for variable-density pressure-gradient-driven turbulence and mixing

International Nuclear Information System (INIS)

Bakosi, Jozsef; Ristorcelli, Raymond J.

2010-01-01

Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.

Collision Probability Analysis

DEFF Research Database (Denmark)

Hansen, Peter Friis; Pedersen, Preben Terndrup

1998-01-01

It is the purpose of this report to apply a rational model for prediction of ship-ship collision probabilities as function of the ship and the crew characteristics and the navigational environment for MS Dextra sailing on a route between Cadiz and the Canary Islands.The most important ship and crew...... characteristics are: ship speed, ship manoeuvrability, the layout of the navigational bridge, the radar system, the number and the training of navigators, the presence of a look out etc. The main parameters affecting the navigational environment are ship traffic density, probability distributions of wind speeds...... probability, i.e. a study of the navigator's role in resolving critical situations, a causation factor is derived as a second step.The report documents the first step in a probabilistic collision damage analysis. Future work will inlcude calculation of energy released for crushing of structures giving...

Irreversibility and conditional probability

International Nuclear Information System (INIS)

Stuart, C.I.J.M.

1989-01-01

The mathematical entropy - unlike physical entropy - is simply a measure of uniformity for probability distributions in general. So understood, conditional entropies have the same logical structure as conditional probabilities. If, as is sometimes supposed, conditional probabilities are time-reversible, then so are conditional entropies and, paradoxically, both then share this symmetry with physical equations of motion. The paradox is, of course that probabilities yield a direction to time both in statistical mechanics and quantum mechanics, while the equations of motion do not. The supposed time-reversibility of both conditionals seems also to involve a form of retrocausality that is related to, but possibly not the same as, that described by Costa de Beaurgard. The retrocausality is paradoxically at odds with the generally presumed irreversibility of the quantum mechanical measurement process. Further paradox emerges if the supposed time-reversibility of the conditionals is linked with the idea that the thermodynamic entropy is the same thing as 'missing information' since this confounds the thermodynamic and mathematical entropies. However, it is shown that irreversibility is a formal consequence of conditional entropies and, hence, of conditional probabilities also. 8 refs. (Author)

Introduction to tensorial resistivity probability tomography

OpenAIRE

Mauriello, Paolo; Patella, Domenico

2005-01-01

The probability tomography approach developed for the scalar resistivity method is here extended to the 2D tensorial apparent resistivity acquisition mode. The rotational invariant derived from the trace of the apparent resistivity tensor is considered, since it gives on the datum plane anomalies confined above the buried objects. Firstly, a departure function is introduced as the difference between the tensorial invariant measured over the real structure and that computed for a reference uni...

Spatial probability of soil water repellency in an abandoned agricultural field in Lithuania

Science.gov (United States)

Pereira, Paulo; Misiūnė, Ieva

2015-04-01

Water repellency is a natural soil property with implications on infiltration, erosion and plant growth. It depends on soil texture, type and amount of organic matter, fungi, microorganisms, and vegetation cover (Doerr et al., 2000). Human activities as agriculture can have implications on soil water repellency (SWR) due tillage and addition of organic compounds and fertilizers (Blanco-Canqui and Lal, 2009; Gonzalez-Penaloza et al., 2012). It is also assumed that SWR has a high small-scale variability (Doerr et al., 2000). The aim of this work is to study the spatial probability of SWR in an abandoned field testing several geostatistical methods, Organic Kriging (OK), Simple Kriging (SK), Indicator Kriging (IK), Probability Kriging (PK) and Disjunctive Kriging (DK). The study area it is located near Vilnius urban area at (54 49' N, 25 22', 104 masl) in Lithuania (Pereira and Oliva, 2013). It was designed a experimental plot with 21 m2 (07x03 m). Inside this area it was measured SWR was measured every 50 cm using the water drop penetration time (WDPT) (Wessel, 1998). A total of 105 points were measured. The probability of SWR was classified in 0 (No probability) to 1 (High probability). The methods accuracy was assessed with the cross validation method. The best interpolation method was the one with the lowest Root Mean Square Error (RMSE). The results showed that the most accurate probability method was SK (RMSE=0.436), followed by DK (RMSE=0.437), IK (RMSE=0.448), PK (RMSE=0.452) and OK (RMSE=0.537). Significant differences were identified among probability tests (Kruskal-Wallis test =199.7597 ptested technique. Simple Kriging, DK, IK and PK methods identified the high SWR probabilities in the northeast and central part of the plot, while OK observed mainly in the south-western part of the plot. In conclusion, before predict the spatial probability of SWR it is important to test several methods in order to identify the most accurate. Acknowledgments COST action ES

Introduction to probability with Mathematica

CERN Document Server

Hastings, Kevin J

2009-01-01

Discrete ProbabilityThe Cast of Characters Properties of Probability Simulation Random SamplingConditional ProbabilityIndependenceDiscrete DistributionsDiscrete Random Variables, Distributions, and ExpectationsBernoulli and Binomial Random VariablesGeometric and Negative Binomial Random Variables Poisson DistributionJoint, Marginal, and Conditional Distributions More on ExpectationContinuous ProbabilityFrom the Finite to the (Very) Infinite Continuous Random Variables and DistributionsContinuous ExpectationContinuous DistributionsThe Normal Distribution Bivariate Normal DistributionNew Random Variables from OldOrder Statistics Gamma DistributionsChi-Square, Student's t, and F-DistributionsTransformations of Normal Random VariablesAsymptotic TheoryStrong and Weak Laws of Large Numbers Central Limit TheoremStochastic Processes and ApplicationsMarkov ChainsPoisson Processes QueuesBrownian MotionFinancial MathematicsAppendixIntroduction to Mathematica Glossary of Mathematica Commands for Probability Short Answers...

Measuring public opinion on alcohol policy: a factor analytic study of a US probability sample.

Science.gov (United States)

Latimer, William W; Harwood, Eileen M; Newcomb, Michael D; Wagenaar, Alexander C

2003-03-01

Public opinion has been one factor affecting change in policies designed to reduce underage alcohol use. Extant research, however, has been criticized for using single survey items of unknown reliability to define adult attitudes on alcohol policy issues. The present investigation addresses a critical gap in the literature by deriving scales on public attitudes, knowledge, and concerns pertinent to alcohol policies designed to reduce underage drinking using a US probability sample survey of 7021 adults. Five attitudinal scales were derived from exploratory and confirmatory factor analyses addressing policies to: (1) regulate alcohol marketing, (2) regulate alcohol consumption in public places, (3) regulate alcohol distribution, (4) increase alcohol taxes, and (5) regulate youth access. The scales exhibited acceptable psychometric properties and were largely consistent with a rational framework which guided the survey construction.

Failure probability under parameter uncertainty.

Science.gov (United States)

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

Energy Technology Data Exchange (ETDEWEB)

Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)

2014-06-19

This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

Blood pressure regulation in diabetic autonomic neuropathy

DEFF Research Database (Denmark)

Hilsted, J

1985-01-01

Defective blood pressure responses to standing, exercise and epinephrine infusions have been demonstrated in diabetic patients with autonomic neuropathy. The circulatory mechanisms underlying blood pressure responses to exercise and standing up in these patients are well characterized: In both...... which may contribute to exercise hypotension in these patients. During hypoglycemia, blood pressure regulation seems intact in patients with autonomic neuropathy. This is probably due to release of substantial amounts of catecholamines during these experiments. During epinephrine infusions a substantial...... blood pressure fall ensues in patients with autonomic neuropathy, probably due to excessive muscular vasodilation. It is unresolved why blood pressure regulation is intact during hypoglycemia and severely impaired--at similar catecholamine concentrations--during epinephrine infusions....

Approaches to Evaluating Probability of Collision Uncertainty

Science.gov (United States)

Hejduk, Matthew D.; Johnson, Lauren C.

2016-01-01

While the two-dimensional probability of collision (Pc) calculation has served as the main input to conjunction analysis risk assessment for over a decade, it has done this mostly as a point estimate, with relatively little effort made to produce confidence intervals on the Pc value based on the uncertainties in the inputs. The present effort seeks to try to carry these uncertainties through the calculation in order to generate a probability density of Pc results rather than a single average value. Methods for assessing uncertainty in the primary and secondary objects' physical sizes and state estimate covariances, as well as a resampling approach to reveal the natural variability in the calculation, are presented; and an initial proposal for operationally-useful display and interpretation of these data for a particular conjunction is given.

Conditional Probability Modulates Visual Search Efficiency

Directory of Open Access Journals (Sweden)

Bryan eCort

2013-10-01

Full Text Available We investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve target detection. We hypothesized that performance improvements from probability information would extend to the efficiency of visual search. Our task was a simple visual search in which the target was always present among a field of distractors, and could take one of two colors. The absolute probability of the target being either color was 0.5; however, the conditional probability – the likelihood of a particular color given a particular combination of two cues – varied from 0.1 to 0.9. We found that participants searched more efficiently for high conditional probability targets and less efficiently for low conditional probability targets, but only when they were explicitly informed of the probability relationship between cues and target color.

A quantum probability model of causal reasoning

Directory of Open Access Journals (Sweden)

Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

Probability and rational choice

Directory of Open Access Journals (Sweden)

David Botting

2014-05-01

Full Text Available http://dx.doi.org/10.5007/1808-1711.2014v18n1p1 In this paper I will discuss the rationality of reasoning about the future. There are two things that we might like to know about the future: which hypotheses are true and what will happen next. To put it in philosophical language, I aim to show that there are methods by which inferring to a generalization (selecting a hypothesis and inferring to the next instance (singular predictive inference can be shown to be normative and the method itself shown to be rational, where this is due in part to being based on evidence (although not in the same way and in part on a prior rational choice. I will also argue that these two inferences have been confused, being distinct not only conceptually (as nobody disputes but also in their results (the value given to the probability of the hypothesis being not in general that given to the next instance and that methods that are adequate for one are not by themselves adequate for the other. A number of debates over method founder on this confusion and do not show what the debaters think they show.

Probability and statistics for particle physics

CERN Document Server

Mana, Carlos

2017-01-01

This book comprehensively presents the basic concepts of probability and Bayesian inference with sufficient generality to make them applicable to current problems in scientific research. The first chapter provides the fundamentals of probability theory that are essential for the analysis of random phenomena. The second chapter includes a full and pragmatic review of the Bayesian methods that constitute a natural and coherent framework with enough freedom to analyze all the information available from experimental data in a conceptually simple manner. The third chapter presents the basic Monte Carlo techniques used in scientific research, allowing a large variety of problems to be handled difficult to tackle by other procedures. The author also introduces a basic algorithm, which enables readers to simulate samples from simple distribution, and describes useful cases for researchers in particle physics.The final chapter is devoted to the basic ideas of Information Theory, which are important in the Bayesian me...

Probability estimation of potential harm to human health and life caused by a hypothetical nuclear accident at the nuclear power plant

International Nuclear Information System (INIS)

Soloviov, Vladyslav; Pysmenniy, Yevgen

2015-01-01

This paper describes some general methodological aspects of the assessment of the damage to human life and health caused by a hypothetical nuclear accident at the nuclear power plant (NPP). Probability estimation of death (due to cancer and non-cancer effects of radiation injury), disability and incapacity of individuals were made by taking into account the regulations of Ukraine. According to the assessment, the probability of death due to cancer and non-cancer effects of radiation damage to individuals who received radiation dose of 1 Sv is equal to 0.09. Probability of disability of 1, 2 or 3 group regardless of the radiation dose is 0.009, 0.0054, 0.027, respectively. Probability of temporary disability of the individual who received dose equal to 33 mSv (the level of potential exposure in a hypothetical nuclear accident at the NPP) is equal 0.16. This probability estimation of potential harm to human health and life caused by a hypothetical nuclear accident can be used for NPP in different countries using requirements of regulations in these countries. And also to estimate the amount of insurance payments due to the nuclear damage in the event of a nuclear accident at the NPP or other nuclear industry enterprise. (author)

A general ray-tracing algorithm for the solution of the neutron transport equation by the collision probability method

International Nuclear Information System (INIS)

Ball, G.

1990-01-01

The development and analysis of methods for generating first-flight collision probabilities in two-dimensional geometries consistent with Light Water Moderated (LWR) fuel assemblies are examined. A new ray-tracing algorithm is discussed. A number of numerical results are given demonstrating the feasibility of this algorithm and the effects of the moderator (and fuel) sectorizations on the resulting flux distributions. The collision probabilties have been introduced and their subsequent utilization in the flux calculation procedures illustrated. A brief description of the Coxy-1 and Coxy-2 programs (which were developed in the Reactor Theory Division of the Atomic Energy Agency of South Africa Ltd) has also been added. 41 figs., 9 tabs., 18 refs