Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

Science.gov (United States)

Olives, Casey; Valadez, Joseph J; Pagano, Marcello

2014-03-01

To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria. We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states. Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high. Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size. © 2014 John Wiley & Sons Ltd.

Evaluation of sampling strategies to estimate crown biomass

Directory of Open Access Journals (Sweden)

Krishna P Poudel

2015-01-01

Full Text Available Background Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. Thus the allometric equations used for predicting crown biomass should be based on data collected with precise and unbiased sampling strategies. In this study, we evaluate the performance different sampling strategies to estimate crown biomass and to evaluate the effect of sample size in estimating crown biomass. Methods Using data collected from 20 destructively sampled trees, we evaluated 11 different sampling strategies using six evaluation statistics: bias, relative bias, root mean square error (RMSE, relative RMSE, amount of biomass sampled, and relative biomass sampled. We also evaluated the performance of the selected sampling strategies when different numbers of branches (3, 6, 9, and 12 are selected from each tree. Tree specific log linear model with branch diameter and branch length as covariates was used to obtain individual branch biomass. Results Compared to all other methods stratified sampling with probability proportional to size estimation technique produced better results when three or six branches per tree were sampled. However, the systematic sampling with ratio estimation technique was the best when at least nine branches per tree were sampled. Under the stratified sampling strategy, selecting unequal number of branches per stratum produced approximately similar results to simple random sampling, but it further decreased RMSE when information on branch diameter is used in the design and estimation phases. Conclusions Use of

Estimation of AUC or Partial AUC under Test-Result-Dependent Sampling.

Science.gov (United States)

Wang, Xiaofei; Ma, Junling; George, Stephen; Zhou, Haibo

2012-01-01

The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.

Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme

Directory of Open Access Journals (Sweden)

Martinásková Magdalena

2017-12-01

Full Text Available The article examines the use of Asymptotic Sampling (AS for the estimation of failure probability. The AS algorithm requires samples of multidimensional Gaussian random vectors, which may be obtained by many alternative means that influence the performance of the AS method. Several reliability problems (test functions have been selected in order to test AS with various sampling schemes: (i Monte Carlo designs; (ii LHS designs optimized using the Periodic Audze-Eglājs (PAE criterion; (iii designs prepared using Sobol’ sequences. All results are compared with the exact failure probability value.

An unbiased estimator of the variance of simple random sampling using mixed random-systematic sampling

OpenAIRE

Padilla, Alberto

2009-01-01

Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. By means of a mixed random - systematic sample, an unbiased estimator o...

Systematic sampling of discrete and continuous populations: sample selection and the choice of estimator

Science.gov (United States)

Harry T. Valentine; David L. R. Affleck; Timothy G. Gregoire

2009-01-01

Systematic sampling is easy, efficient, and widely used, though it is not generally recognized that a systematic sample may be drawn from the population of interest with or without restrictions on randomization. The restrictions or the lack of them determine which estimators are unbiased, when using the sampling design as the basis for inference. We describe the...

Outcome-Dependent Sampling Design and Inference for Cox's Proportional Hazards Model.

Science.gov (United States)

Yu, Jichang; Liu, Yanyan; Cai, Jianwen; Sandler, Dale P; Zhou, Haibo

2016-11-01

We propose a cost-effective outcome-dependent sampling design for the failure time data and develop an efficient inference procedure for data collected with this design. To account for the biased sampling scheme, we derive estimators from a weighted partial likelihood estimating equation. The proposed estimators for regression parameters are shown to be consistent and asymptotically normally distributed. A criteria that can be used to optimally implement the ODS design in practice is proposed and studied. The small sample performance of the proposed method is evaluated by simulation studies. The proposed design and inference procedure is shown to be statistically more powerful than existing alternative designs with the same sample sizes. We illustrate the proposed method with an existing real data from the Cancer Incidence and Mortality of Uranium Miners Study.

Statistical Methods and Sampling Design for Estimating Step Trends in Surface-Water Quality

Science.gov (United States)

Hirsch, Robert M.

1988-01-01

This paper addresses two components of the problem of estimating the magnitude of step trends in surface water quality. The first is finding a robust estimator appropriate to the data characteristics expected in water-quality time series. The J. L. Hodges-E. L. Lehmann class of estimators is found to be robust in comparison to other nonparametric and moment-based estimators. A seasonal Hodges-Lehmann estimator is developed and shown to have desirable properties. Second, the effectiveness of various sampling strategies is examined using Monte Carlo simulation coupled with application of this estimator. The simulation is based on a large set of total phosphorus data from the Potomac River. To assure that the simulated records have realistic properties, the data are modeled in a multiplicative fashion incorporating flow, hysteresis, seasonal, and noise components. The results demonstrate the importance of balancing the length of the two sampling periods and balancing the number of data values between the two periods.

Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

Science.gov (United States)

Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.

2013-12-01

Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses

Estimation of sample size and testing power (Part 3).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2011-12-01

This article introduces the definition and sample size estimation of three special tests (namely, non-inferiority test, equivalence test and superiority test) for qualitative data with the design of one factor with two levels having a binary response variable. Non-inferiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is not clinically inferior to that of the positive control drug. Equivalence test refers to the research design of which the objective is to verify that the experimental drug and the control drug have clinically equivalent efficacy. Superiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is clinically superior to that of the control drug. By specific examples, this article introduces formulas of sample size estimation for the three special tests, and their SAS realization in detail.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

Science.gov (United States)

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

Design-based estimators for snowball sampling

OpenAIRE

Shafie, Termeh

2010-01-01

Snowball sampling, where existing study subjects recruit further subjects from amongtheir acquaintances, is a popular approach when sampling from hidden populations.Since people with many in-links are more likely to be selected, there will be a selectionbias in the samples obtained. In order to eliminate this bias, the sample data must beweighted. However, the exact selection probabilities are unknown for snowball samplesand need to be approximated in an appropriate way. This paper proposes d...

Outcome-Dependent Sampling Design and Inference for Cox’s Proportional Hazards Model

Science.gov (United States)

Yu, Jichang; Liu, Yanyan; Cai, Jianwen; Sandler, Dale P.; Zhou, Haibo

2016-01-01

We propose a cost-effective outcome-dependent sampling design for the failure time data and develop an efficient inference procedure for data collected with this design. To account for the biased sampling scheme, we derive estimators from a weighted partial likelihood estimating equation. The proposed estimators for regression parameters are shown to be consistent and asymptotically normally distributed. A criteria that can be used to optimally implement the ODS design in practice is proposed and studied. The small sample performance of the proposed method is evaluated by simulation studies. The proposed design and inference procedure is shown to be statistically more powerful than existing alternative designs with the same sample sizes. We illustrate the proposed method with an existing real data from the Cancer Incidence and Mortality of Uranium Miners Study. PMID:28090134

Estimating time to pregnancy from current durations in a cross-sectional sample

DEFF Research Database (Denmark)

Keiding, Niels; Kvist, Kajsa; Hartvig, Helle

2002-01-01

A new design for estimating the distribution of time to pregnancy is proposed and investigated. The design is based on recording current durations in a cross-sectional sample of women, leading to statistical problems similar to estimating renewal time distributions from backward recurrence times....

Maximum likelihood estimation for Cox's regression model under nested case-control sampling

DEFF Research Database (Denmark)

Scheike, Thomas; Juul, Anders

2004-01-01

Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazard...

Development of a sampling strategy and sample size calculation to estimate the distribution of mammographic breast density in Korean women.

Science.gov (United States)

Jun, Jae Kwan; Kim, Mi Jin; Choi, Kui Son; Suh, Mina; Jung, Kyu-Won

2012-01-01

Mammographic breast density is a known risk factor for breast cancer. To conduct a survey to estimate the distribution of mammographic breast density in Korean women, appropriate sampling strategies for representative and efficient sampling design were evaluated through simulation. Using the target population from the National Cancer Screening Programme (NCSP) for breast cancer in 2009, we verified the distribution estimate by repeating the simulation 1,000 times using stratified random sampling to investigate the distribution of breast density of 1,340,362 women. According to the simulation results, using a sampling design stratifying the nation into three groups (metropolitan, urban, and rural), with a total sample size of 4,000, we estimated the distribution of breast density in Korean women at a level of 0.01% tolerance. Based on the results of our study, a nationwide survey for estimating the distribution of mammographic breast density among Korean women can be conducted efficiently.

Reliability of impingement sampling designs: An example from the Indian Point station

International Nuclear Information System (INIS)

Mattson, M.T.; Waxman, J.B.; Watson, D.A.

1988-01-01

A 4-year data base (1976-1979) of daily fish impingement counts at the Indian Point electric power station on the Hudson River was used to compare the precision and reliability of three random-sampling designs: (1) simple random, (2) seasonally stratified, and (3) empirically stratified. The precision of daily impingement estimates improved logarithmically for each design as more days in the year were sampled. Simple random sampling was the least, and empirically stratified sampling was the most precise design, and the difference in precision between the two stratified designs was small. Computer-simulated sampling was used to estimate the reliability of the two stratified-random-sampling designs. A seasonally stratified sampling design was selected as the most appropriate reduced-sampling program for Indian Point station because: (1) reasonably precise and reliable impingement estimates were obtained using this design for all species combined and for eight common Hudson River fish by sampling only 30% of the days in a year (110 d); and (2) seasonal strata may be more precise and reliable than empirical strata if future changes in annual impingement patterns occur. The seasonally stratified design applied to the 1976-1983 Indian Point impingement data showed that selection of sampling dates based on daily species-specific impingement variability gave results that were more precise, but not more consistently reliable, than sampling allocations based on the variability of all fish species combined. 14 refs., 1 fig., 6 tabs

Sampling and estimating recreational use.

Science.gov (United States)

Timothy G. Gregoire; Gregory J. Buhyoff

1999-01-01

Probability sampling methods applicable to estimate recreational use are presented. Both single- and multiple-access recreation sites are considered. One- and two-stage sampling methods are presented. Estimation of recreational use is presented in a series of examples.

Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives

Science.gov (United States)

2013-01-01

Background The emergence of Plasmodium falciparum resistance to artemisinins in Southeast Asia threatens the control of malaria worldwide. The pharmacodynamic hallmark of artemisinin derivatives is rapid parasite clearance (a short parasite half-life), therefore, the in vivo phenotype of slow clearance defines the reduced susceptibility to the drug. Measurement of parasite counts every six hours during the first three days after treatment have been recommended to measure the parasite clearance half-life, but it remains unclear whether simpler sampling intervals and frequencies might also be sufficient to reliably estimate this parameter. Methods A total of 2,746 parasite density-time profiles were selected from 13 clinical trials in Thailand, Cambodia, Mali, Vietnam, and Kenya. In these studies, parasite densities were measured every six hours until negative after treatment with an artemisinin derivative (alone or in combination with a partner drug). The WWARN Parasite Clearance Estimator (PCE) tool was used to estimate “reference” half-lives from these six-hourly measurements. The effect of four alternative sampling schedules on half-life estimation was investigated, and compared to the reference half-life (time zero, 6, 12, 24 (A1); zero, 6, 18, 24 (A2); zero, 12, 18, 24 (A3) or zero, 12, 24 (A4) hours and then every 12 hours). Statistical bootstrap methods were used to estimate the sampling distribution of half-lives for parasite populations with different geometric mean half-lives. A simulation study was performed to investigate a suite of 16 potential alternative schedules and half-life estimates generated by each of the schedules were compared to the “true” half-life. The candidate schedules in the simulation study included (among others) six-hourly sampling, schedule A1, schedule A4, and a convenience sampling schedule at six, seven, 24, 25, 48 and 49 hours. Results The median (range) parasite half-life for all clinical studies combined was 3.1 (0

Low-sampling-rate ultra-wideband channel estimation using equivalent-time sampling

KAUST Repository

Ballal, Tarig

2014-09-01

In this paper, a low-sampling-rate scheme for ultra-wideband channel estimation is proposed. The scheme exploits multiple observations generated by transmitting multiple pulses. In the proposed scheme, P pulses are transmitted to produce channel impulse response estimates at a desired sampling rate, while the ADC samples at a rate that is P times slower. To avoid loss of fidelity, the number of sampling periods (based on the desired rate) in the inter-pulse interval is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this case, and to achieve an overall good channel estimation performance, without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. It is shown that this estimator is related to the Bayesian linear minimum mean squared error (LMMSE) estimator. Channel estimation performance of the proposed sub-sampling scheme combined with the new estimator is assessed in simulation. The results show that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in almost all cases, while in the high SNR regime it also outperforms the LMMSE estimator. In addition to channel estimation, a synchronization method is also proposed that utilizes the same pulse sequence used for channel estimation. © 2014 IEEE.

Triangulation based inclusion probabilities: a design-unbiased sampling approach

OpenAIRE

Fehrmann, Lutz; Gregoire, Timothy; Kleinn, Christoph

2011-01-01

A probabilistic sampling approach for design-unbiased estimation of area-related quantitative characteristics of spatially dispersed population units is proposed. The developed field protocol includes a fixed number of 3 units per sampling location and is based on partial triangulations over their natural neighbors to derive the individual inclusion probabilities. The performance of the proposed design is tested in comparison to fixed area sample plots in a simulation with two forest stands. ...

Sampling designs matching species biology produce accurate and affordable abundance indices

Directory of Open Access Journals (Sweden)

Grant Harris

2013-12-01

Full Text Available Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e., targeted sampling, it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS data from 42 Alaskan brown bears (Ursus arctos. Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion, and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km2 cells and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture

Sampling designs matching species biology produce accurate and affordable abundance indices.

Science.gov (United States)

Harris, Grant; Farley, Sean; Russell, Gareth J; Butler, Matthew J; Selinger, Jeff

2013-01-01

Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e., targeted sampling), it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS) data from 42 Alaskan brown bears (Ursus arctos). Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion), and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km(2) cells) and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture sessions

Sampling designs matching species biology produce accurate and affordable abundance indices

Science.gov (United States)

Farley, Sean; Russell, Gareth J.; Butler, Matthew J.; Selinger, Jeff

2013-01-01

Wildlife biologists often use grid-based designs to sample animals and generate abundance estimates. Although sampling in grids is theoretically sound, in application, the method can be logistically difficult and expensive when sampling elusive species inhabiting extensive areas. These factors make it challenging to sample animals and meet the statistical assumption of all individuals having an equal probability of capture. Violating this assumption biases results. Does an alternative exist? Perhaps by sampling only where resources attract animals (i.e., targeted sampling), it would provide accurate abundance estimates more efficiently and affordably. However, biases from this approach would also arise if individuals have an unequal probability of capture, especially if some failed to visit the sampling area. Since most biological programs are resource limited, and acquiring abundance data drives many conservation and management applications, it becomes imperative to identify economical and informative sampling designs. Therefore, we evaluated abundance estimates generated from grid and targeted sampling designs using simulations based on geographic positioning system (GPS) data from 42 Alaskan brown bears (Ursus arctos). Migratory salmon drew brown bears from the wider landscape, concentrating them at anadromous streams. This provided a scenario for testing the targeted approach. Grid and targeted sampling varied by trap amount, location (traps placed randomly, systematically or by expert opinion), and traps stationary or moved between capture sessions. We began by identifying when to sample, and if bears had equal probability of capture. We compared abundance estimates against seven criteria: bias, precision, accuracy, effort, plus encounter rates, and probabilities of capture and recapture. One grid (49 km2 cells) and one targeted configuration provided the most accurate results. Both placed traps by expert opinion and moved traps between capture sessions, which

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

Science.gov (United States)

Goudet, Jérôme; Büchi, Lucie

2006-02-01

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Sample size estimation and sampling techniques for selecting a representative sample

Directory of Open Access Journals (Sweden)

Aamir Omair

2014-01-01

Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

Estimation of sample size and testing power (part 6).

Science.gov (United States)

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-03-01

The design of one factor with k levels (k ≥ 3) refers to the research that only involves one experimental factor with k levels (k ≥ 3), and there is no arrangement for other important non-experimental factors. This paper introduces the estimation of sample size and testing power for quantitative data and qualitative data having a binary response variable with the design of one factor with k levels (k ≥ 3).

B-graph sampling to estimate the size of a hidden population

NARCIS (Netherlands)

Spreen, M.; Bogaerts, S.

2015-01-01

Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is

Estimates and sampling schemes for the instrumentation of accountability systems

International Nuclear Information System (INIS)

Jewell, W.S.; Kwiatkowski, J.W.

1976-10-01

The problem of estimation of a physical quantity from a set of measurements is considered, where the measurements are made on samples with a hierarchical error structure, and where within-groups error variances may vary from group to group at each level of the structure; minimum mean squared-error estimators are developed, and the case where the physical quantity is a random variable with known prior mean and variance is included. Estimators for the error variances are also given, and optimization of experimental design is considered

Estimation of river and stream temperature trends under haphazard sampling

Science.gov (United States)

Gray, Brian R.; Lyubchich, Vyacheslav; Gel, Yulia R.; Rogala, James T.; Robertson, Dale M.; Wei, Xiaoqiao

2015-01-01

Long-term temporal trends in water temperature in rivers and streams are typically estimated under the assumption of evenly-spaced space-time measurements. However, sampling times and dates associated with historical water temperature datasets and some sampling designs may be haphazard. As a result, trends in temperature may be confounded with trends in time or space of sampling which, in turn, may yield biased trend estimators and thus unreliable conclusions. We address this concern using multilevel (hierarchical) linear models, where time effects are allowed to vary randomly by day and date effects by year. We evaluate the proposed approach by Monte Carlo simulations with imbalance, sparse data and confounding by trend in time and date of sampling. Simulation results indicate unbiased trend estimators while results from a case study of temperature data from the Illinois River, USA conform to river thermal assumptions. We also propose a new nonparametric bootstrap inference on multilevel models that allows for a relatively flexible and distribution-free quantification of uncertainties. The proposed multilevel modeling approach may be elaborated to accommodate nonlinearities within days and years when sampling times or dates typically span temperature extremes.

Off-road sampling reveals a different grassland bird community than roadside sampling: implications for survey design and estimates to guide conservation

Directory of Open Access Journals (Sweden)

Troy I. Wellicome

2014-06-01

concern. Our results highlight the need to develop appropriate corrections for bias in estimates derived from roadside sampling, and the need to design surveys that sample bird communities across a more representative cross-section of the landscape, both near and far from roads.

Critical point relascope sampling for unbiased volume estimation of downed coarse woody debris

Science.gov (United States)

Jeffrey H. Gove; Michael S. Williams; Mark J. Ducey; Mark J. Ducey

2005-01-01

Critical point relascope sampling is developed and shown to be design-unbiased for the estimation of log volume when used with point relascope sampling for downed coarse woody debris. The method is closely related to critical height sampling for standing trees when trees are first sampled with a wedge prism. Three alternative protocols for determining the critical...

The current duration design for estimating the time to pregnancy distribution

DEFF Research Database (Denmark)

Gasbarra, Dario; Arjas, Elja; Vehtari, Aki

2015-01-01

This paper was inspired by the studies of Niels Keiding and co-authors on estimating the waiting time-to-pregnancy (TTP) distribution, and in particular on using the current duration design in that context. In this design, a cross-sectional sample of women is collected from those who are currently...... attempting to become pregnant, and then by recording from each the time she has been attempting. Our aim here is to study the identifiability and the estimation of the waiting time distribution on the basis of current duration data. The main difficulty in this stems from the fact that very short waiting...... times are only rarely selected into the sample of current durations, and this renders their estimation unstable. We introduce here a Bayesian method for this estimation problem, prove its asymptotic consistency, and compare the method to some variants of the non-parametric maximum likelihood estimators...

Influence of Sampling Effort on the Estimated Richness of Road-Killed Vertebrate Wildlife

Science.gov (United States)

Bager, Alex; da Rosa, Clarissa A.

2011-05-01

Road-killed mammals, birds, and reptiles were collected weekly from highways in southern Brazil in 2002 and 2005. The objective was to assess variation in estimates of road-kill impacts on species richness produced by different sampling efforts, and to provide information to aid in the experimental design of future sampling. Richness observed in weekly samples was compared with sampling for different periods. In each period, the list of road-killed species was evaluated based on estimates the community structure derived from weekly samplings, and by the presence of the ten species most subject to road mortality, and also of threatened species. Weekly samples were sufficient only for reptiles and mammals, considered separately. Richness estimated from the biweekly samples was equal to that found in the weekly samples, and gave satisfactory results for sampling the most abundant and threatened species. The ten most affected species showed constant road-mortality rates, independent of sampling interval, and also maintained their dominance structure. Birds required greater sampling effort. When the composition of road-killed species varies seasonally, it is necessary to take biweekly samples for a minimum of one year. Weekly or more-frequent sampling for periods longer than two years is necessary to provide a reliable estimate of total species richness.

Simulation methods to estimate design power: an overview for applied research.

Science.gov (United States)

Arnold, Benjamin F; Hogan, Daniel R; Colford, John M; Hubbard, Alan E

2011-06-20

Estimating the required sample size and statistical power for a study is an integral part of study design. For standard designs, power equations provide an efficient solution to the problem, but they are unavailable for many complex study designs that arise in practice. For such complex study designs, computer simulation is a useful alternative for estimating study power. Although this approach is well known among statisticians, in our experience many epidemiologists and social scientists are unfamiliar with the technique. This article aims to address this knowledge gap. We review an approach to estimate study power for individual- or cluster-randomized designs using computer simulation. This flexible approach arises naturally from the model used to derive conventional power equations, but extends those methods to accommodate arbitrarily complex designs. The method is universally applicable to a broad range of designs and outcomes, and we present the material in a way that is approachable for quantitative, applied researchers. We illustrate the method using two examples (one simple, one complex) based on sanitation and nutritional interventions to improve child growth. We first show how simulation reproduces conventional power estimates for simple randomized designs over a broad range of sample scenarios to familiarize the reader with the approach. We then demonstrate how to extend the simulation approach to more complex designs. Finally, we discuss extensions to the examples in the article, and provide computer code to efficiently run the example simulations in both R and Stata. Simulation methods offer a flexible option to estimate statistical power for standard and non-traditional study designs and parameters of interest. The approach we have described is universally applicable for evaluating study designs used in epidemiologic and social science research.

The test-negative design for estimating influenza vaccine effectiveness.

Science.gov (United States)

Jackson, Michael L; Nelson, Jennifer C

2013-04-19

The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed. In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative. With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time. The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators

KAUST Repository

Kammoun, Abla; Couillet, Romain; Pascal, Frederic; Alouini, Mohamed-Slim

2017-01-01

This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.

Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators

KAUST Repository

Kammoun, Abla

2017-10-25

This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.

Cost-effective sampling of 137Cs-derived net soil redistribution: part 1 – estimating the spatial mean across scales of variation

International Nuclear Information System (INIS)

Li, Y.; Chappell, A.; Nyamdavaa, B.; Yu, H.; Davaasuren, D.; Zoljargal, K.

2015-01-01

The 137 Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many 137 Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of 137 Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954–2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate 137 Cs-derived net soil redistribution across scales of variation. - Highlights: • The 137 Cs technique estimates net time-integrated soil redistribution by all processes. • It is time-consuming and dominated by studies of individual fields. • We use limited resources to estimate soil

Improved sampling for airborne surveys to estimate wildlife population parameters in the African Savannah

NARCIS (Netherlands)

Khaemba, W.; Stein, A.

2002-01-01

Parameter estimates, obtained from airborne surveys of wildlife populations, often have large bias and large standard errors. Sampling error is one of the major causes of this imprecision and the occurrence of many animals in herds violates the common assumptions in traditional sampling designs like

Estimation of the sugar cane cultivated area from LANDSAT images using the two phase sampling method

Science.gov (United States)

Parada, N. D. J. (Principal Investigator); Cappelletti, C. A.; Mendonca, F. J.; Lee, D. C. L.; Shimabukuro, Y. E.

1982-01-01

A two phase sampling method and the optimal sampling segment dimensions for the estimation of sugar cane cultivated area were developed. This technique employs visual interpretations of LANDSAT images and panchromatic aerial photographs considered as the ground truth. The estimates, as a mean value of 100 simulated samples, represent 99.3% of the true value with a CV of approximately 1%; the relative efficiency of the two phase design was 157% when compared with a one phase aerial photographs sample.

Reliability of different sampling densities for estimating and mapping lichen diversity in biomonitoring studies

International Nuclear Information System (INIS)

Ferretti, M.; Brambilla, E.; Brunialti, G.; Fornasier, F.; Mazzali, C.; Giordani, P.; Nimis, P.L.

2004-01-01

Sampling requirements related to lichen biomonitoring include optimal sampling density for obtaining precise and unbiased estimates of population parameters and maps of known reliability. Two available datasets on a sub-national scale in Italy were used to determine a cost-effective sampling density to be adopted in medium-to-large-scale biomonitoring studies. As expected, the relative error in the mean Lichen Biodiversity (Italian acronym: BL) values and the error associated with the interpolation of BL values for (unmeasured) grid cells increased as the sampling density decreased. However, the increase in size of the error was not linear and even a considerable reduction (up to 50%) in the original sampling effort led to a far smaller increase in errors in the mean estimates (<6%) and in mapping (<18%) as compared with the original sampling densities. A reduction in the sampling effort can result in considerable savings of resources, which can then be used for a more detailed investigation of potentially problematic areas. It is, however, necessary to decide the acceptable level of precision at the design stage of the investigation, so as to select the proper sampling density. - An acceptable level of precision must be decided before determining a sampling design

Sample size reassessment for a two-stage design controlling the false discovery rate.

Science.gov (United States)

Zehetmayer, Sonja; Graf, Alexandra C; Posch, Martin

2015-11-01

Sample size calculations for gene expression microarray and NGS-RNA-Seq experiments are challenging because the overall power depends on unknown quantities as the proportion of true null hypotheses and the distribution of the effect sizes under the alternative. We propose a two-stage design with an adaptive interim analysis where these quantities are estimated from the interim data. The second stage sample size is chosen based on these estimates to achieve a specific overall power. The proposed procedure controls the power in all considered scenarios except for very low first stage sample sizes. The false discovery rate (FDR) is controlled despite of the data dependent choice of sample size. The two-stage design can be a useful tool to determine the sample size of high-dimensional studies if in the planning phase there is high uncertainty regarding the expected effect sizes and variability.

Graph Sampling for Covariance Estimation

KAUST Repository

Chepuri, Sundeep Prabhakar

2017-04-25

In this paper the focus is on subsampling as well as reconstructing the second-order statistics of signals residing on nodes of arbitrary undirected graphs. Second-order stationary graph signals may be obtained by graph filtering zero-mean white noise and they admit a well-defined power spectrum whose shape is determined by the frequency response of the graph filter. Estimating the graph power spectrum forms an important component of stationary graph signal processing and related inference tasks such as Wiener prediction or inpainting on graphs. The central result of this paper is that by sampling a significantly smaller subset of vertices and using simple least squares, we can reconstruct the second-order statistics of the graph signal from the subsampled observations, and more importantly, without any spectral priors. To this end, both a nonparametric approach as well as parametric approaches including moving average and autoregressive models for the graph power spectrum are considered. The results specialize for undirected circulant graphs in that the graph nodes leading to the best compression rates are given by the so-called minimal sparse rulers. A near-optimal greedy algorithm is developed to design the subsampling scheme for the non-parametric and the moving average models, whereas a particular subsampling scheme that allows linear estimation for the autoregressive model is proposed. Numerical experiments on synthetic as well as real datasets related to climatology and processing handwritten digits are provided to demonstrate the developed theory.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

Science.gov (United States)

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maximum likelihood estimation for Cox's regression model under nested case-control sampling

DEFF Research Database (Denmark)

Scheike, Thomas Harder; Juul, Anders

2004-01-01

-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used......Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards...... model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin...

Approximating the variance of estimated means for systematic random sampling, illustrated with data of the French Soil Monitoring Network

NARCIS (Netherlands)

Brus, D.J.; Saby, N.P.A.

2016-01-01

In France like in many other countries, the soil is monitored at the locations of a regular, square grid thus forming a systematic sample (SY). This sampling design leads to good spatial coverage, enhancing the precision of design-based estimates of spatial means and totals. Design-based

Estimation of population mean under systematic sampling

Science.gov (United States)

Noor-ul-amin, Muhammad; Javaid, Amjad

2017-11-01

In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.

Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

Science.gov (United States)

Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

Estimating open population site occupancy from presence-absence data lacking the robust design.

Science.gov (United States)

Dail, D; Madsen, L

2013-03-01

Many animal monitoring studies seek to estimate the proportion of a study area occupied by a target population. The study area is divided into spatially distinct sites where the detected presence or absence of the population is recorded, and this is repeated in time for multiple seasons. However, when occupied sites are detected with probability p Ecology 84, 2200-2207) developed a multiseason model for estimating seasonal site occupancy (ψt ) while accounting for unknown p. Their model performs well when observations are collected according to the robust design, where multiple sampling occasions occur during each season; the repeated sampling aids in the estimation p. However, their model does not perform as well when the robust design is lacking. In this paper, we propose an alternative likelihood model that yields improved seasonal estimates of p and Ψt in the absence of the robust design. We construct the marginal likelihood of the observed data by conditioning on, and summing out, the latent number of occupied sites during each season. A simulation study shows that in cases without the robust design, the proposed model estimates p with less bias than the MacKenzie et al. model and hence improves the estimates of Ψt . We apply both models to a data set consisting of repeated presence-absence observations of American robins (Turdus migratorius) with yearly survey periods. The two models are compared to a third estimator available when the repeated counts (from the same study) are considered, with the proposed model yielding estimates of Ψt closest to estimates from the point count model. Copyright © 2013, The International Biometric Society.

Planetary Sample Caching System Design Options

Science.gov (United States)

Collins, Curtis; Younse, Paulo; Backes, Paul

2009-01-01

Potential Mars Sample Return missions would aspire to collect small core and regolith samples using a rover with a sample acquisition tool and sample caching system. Samples would need to be stored in individual sealed tubes in a canister that could be transfered to a Mars ascent vehicle and returned to Earth. A sample handling, encapsulation and containerization system (SHEC) has been developed as part of an integrated system for acquiring and storing core samples for application to future potential MSR and other potential sample return missions. Requirements and design options for the SHEC system were studied and a recommended design concept developed. Two families of solutions were explored: 1)transfer of a raw sample from the tool to the SHEC subsystem and 2)transfer of a tube containing the sample to the SHEC subsystem. The recommended design utilizes sample tool bit change out as the mechanism for transferring tubes to and samples in tubes from the tool. The SHEC subsystem design, called the Bit Changeout Caching(BiCC) design, is intended for operations on a MER class rover.

Analysing designed experiments in distance sampling

Science.gov (United States)

Stephen T. Buckland; Robin E. Russell; Brett G. Dickson; Victoria A. Saab; Donal N. Gorman; William M. Block

2009-01-01

Distance sampling is a survey technique for estimating the abundance or density of wild animal populations. Detection probabilities of animals inherently differ by species, age class, habitats, or sex. By incorporating the change in an observer's ability to detect a particular class of animals as a function of distance, distance sampling leads to density estimates...

A Probabilistic Mass Estimation Algorithm for a Novel 7- Channel Capacitive Sample Verification Sensor

Science.gov (United States)

Wolf, Michael

2012-01-01

A document describes an algorithm created to estimate the mass placed on a sample verification sensor (SVS) designed for lunar or planetary robotic sample return missions. A novel SVS measures the capacitance between a rigid bottom plate and an elastic top membrane in seven locations. As additional sample material (soil and/or small rocks) is placed on the top membrane, the deformation of the membrane increases the capacitance. The mass estimation algorithm addresses both the calibration of each SVS channel, and also addresses how to combine the capacitances read from each of the seven channels into a single mass estimate. The probabilistic approach combines the channels according to the variance observed during the training phase, and provides not only the mass estimate, but also a value for the certainty of the estimate. SVS capacitance data is collected for known masses under a wide variety of possible loading scenarios, though in all cases, the distribution of sample within the canister is expected to be approximately uniform. A capacitance-vs-mass curve is fitted to this data, and is subsequently used to determine the mass estimate for the single channel s capacitance reading during the measurement phase. This results in seven different mass estimates, one for each SVS channel. Moreover, the variance of the calibration data is used to place a Gaussian probability distribution function (pdf) around this mass estimate. To blend these seven estimates, the seven pdfs are combined into a single Gaussian distribution function, providing the final mean and variance of the estimate. This blending technique essentially takes the final estimate as an average of the estimates of the seven channels, weighted by the inverse of the channel s variance.

An Improvement to Interval Estimation for Small Samples

Directory of Open Access Journals (Sweden)

SUN Hui-Ling

2017-02-01

Full Text Available Because it is difficult and complex to determine the probability distribution of small samples，it is improper to use traditional probability theory to process parameter estimation for small samples. Bayes Bootstrap method is always used in the project. Although，the Bayes Bootstrap method has its own limitation，In this article an improvement is given to the Bayes Bootstrap method，This method extended the amount of samples by numerical simulation without changing the circumstances in a small sample of the original sample. And the new method can give the accurate interval estimation for the small samples. Finally，by using the Monte Carlo simulation to model simulation to the specific small sample problems. The effectiveness and practicability of the Improved-Bootstrap method was proved.

A geostatistical estimation of zinc grade in bore-core samples

International Nuclear Information System (INIS)

Starzec, A.

1987-01-01

Possibilities and preliminary results of geostatistical interpretation of the XRF determination of zinc in bore-core samples are considered. For the spherical model of the variogram the estimation variance of grade in a disk-shape sample (estimated from the grade on the circumference sample) is calculated. Variograms of zinc grade in core samples are presented and examples of the grade estimation are discussed. 4 refs., 7 figs., 1 tab. (author)

A Web-based Simulator for Sample Size and Power Estimation in Animal Carcinogenicity Studies

Directory of Open Access Journals (Sweden)

Hojin Moon

2002-12-01

Full Text Available A Web-based statistical tool for sample size and power estimation in animal carcinogenicity studies is presented in this paper. It can be used to provide a design with sufficient power for detecting a dose-related trend in the occurrence of a tumor of interest when competing risks are present. The tumors of interest typically are occult tumors for which the time to tumor onset is not directly observable. It is applicable to rodent tumorigenicity assays that have either a single terminal sacrifice or multiple (interval sacrifices. The design is achieved by varying sample size per group, number of sacrifices, number of sacrificed animals at each interval, if any, and scheduled time points for sacrifice. Monte Carlo simulation is carried out in this tool to simulate experiments of rodent bioassays because no closed-form solution is available. It takes design parameters for sample size and power estimation as inputs through the World Wide Web. The core program is written in C and executed in the background. It communicates with the Web front end via a Component Object Model interface passing an Extensible Markup Language string. The proposed statistical tool is illustrated with an animal study in lung cancer prevention research.

Temporally stratified sampling programs for estimation of fish impingement

International Nuclear Information System (INIS)

Kumar, K.D.; Griffith, J.S.

1977-01-01

Impingement monitoring programs often expend valuable and limited resources and fail to provide a dependable estimate of either total annual impingement or those biological and physicochemical factors affecting impingement. In situations where initial monitoring has identified ''problem'' fish species and the periodicity of their impingement, intensive sampling during periods of high impingement will maximize information obtained. We use data gathered at two nuclear generating facilities in the southeastern United States to discuss techniques of designing such temporally stratified monitoring programs and their benefits and drawbacks. Of the possible temporal patterns in environmental factors within a calendar year, differences among seasons are most influential in the impingement of freshwater fishes in the Southeast. Data on the threadfin shad (Dorosoma petenense) and the role of seasonal temperature changes are utilized as an example to demonstrate ways of most efficiently and accurately estimating impingement of the species

Poisson sampling - The adjusted and unadjusted estimator revisited

Science.gov (United States)

Michael S. Williams; Hans T. Schreuder; Gerardo H. Terrazas

1998-01-01

The prevailing assumption, that for Poisson sampling the adjusted estimator "Y-hat a" is always substantially more efficient than the unadjusted estimator "Y-hat u" , is shown to be incorrect. Some well known theoretical results are applicable since "Y-hat a" is a ratio-of-means estimator and "Y-hat u" a simple unbiased estimator...

Estimating Large Area Forest Carbon Stocks—A Pragmatic Design Based Strategy

Directory of Open Access Journals (Sweden)

Andrew Haywood

2017-03-01

Full Text Available Reducing uncertainty in forest carbon estimates at local and regional scales has become increasingly important due to the centrality of the terrestrial carbon cycle in issues of climate change. In Victoria, Australia, public natural forests extend over 7.2 M ha and constitute a significant and important carbon stock. Recently, a wide range of approaches to estimate carbon stocks within these forests have been developed and applied. However, there are a number of data and estimation limitations associated with these studies. In response, over the last five years, the State of Victoria has implemented a pragmatic plot-based design consisting of pre-stratified permanent observational units located on a state-wide grid. Using the ground sampling grid, we estimated aboveground and belowground carbon stocks (including soil to 0.3 m depth in both National Parks and State Forests, across a wide range of bioregions. Estimates of carbon stocks and associated uncertainty were conducted using simple design based estimators. We detected significantly more carbon in total aboveground and belowground components in State Forests (408.9 t ha−1, 95% confidence interval 388.8–428.9 t ha−1 than National Parks (267.6 t ha−1, 251.9–283.3 t ha−1. We were also able to estimate forest carbon stocks (and associated uncertainty for 21 strata that represent all of Victoria’s bioregions and public tenures. It is anticipated that the lessons learnt from this study may support the discussion on planning and implementing low cost large area forest carbon stock sampling in other jurisdictions.

Power Spectrum Estimation of Randomly Sampled Signals

DEFF Research Database (Denmark)

Velte, C. M.; Buchhave, P.; K. George, W.

algorithms; sample and-hold and the direct spectral estimator without residence time weighting. The computer generated signal is a Poisson process with a sample rate proportional to velocity magnitude that consist of well-defined frequency content, which makes bias easy to spot. The idea...

Efficient estimation for ergodic diffusions sampled at high frequency

DEFF Research Database (Denmark)

Sørensen, Michael

A general theory of efficient estimation for ergodic diffusions sampled at high fre- quency is presented. High frequency sampling is now possible in many applications, in particular in finance. The theory is formulated in term of approximate martingale estimating functions and covers a large class...

Comparing interval estimates for small sample ordinal CFA models.

Science.gov (United States)

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading

Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights.

Directory of Open Access Journals (Sweden)

Patrick Habecker

Full Text Available Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations via traditional survey tools such as telephone or mail surveys--by asking a representative sample to estimate the number of people they know who are members of such a "hidden" subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation "trimming" to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.

Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.

Energy Technology Data Exchange (ETDEWEB)

Matulef, Kevin Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewer resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.

Estimation of creatinine in Urine sample by Jaffe's method

International Nuclear Information System (INIS)

Wankhede, Sonal; Arunkumar, Suja; Sawant, Pramilla D.; Rao, B.B.

2012-01-01

In-vitro bioassay monitoring is based on the determination of activity concentrations in biological samples excreted from the body and is most suitable for alpha and beta emitters. A truly representative bioassay sample is the one having all the voids collected during a 24-h period however, this being technically difficult, overnight urine samples collected by the workers are analyzed. These overnight urine samples are collected for 10-16 h, however in the absence of any specific information, 12 h duration is assumed and the observed results are then corrected accordingly obtain the daily excretion rate. To reduce the uncertainty due to unknown duration of sample collection, IAEA has recommended two methods viz., measurement of specific gravity and creatinine excretion rate in urine sample. Creatinine is a final metabolic product creatinine phosphate in the body and is excreted at a steady rate for people with normally functioning kidneys. It is, therefore, often used as a normalization factor for estimation of duration of sample collection. The present study reports the chemical procedure standardized and its application for the estimation of creatinine in urine samples collected from occupational workers. Chemical procedure for estimation of creatinine in bioassay samples was standardized and applied successfully for its estimation in bioassay samples collected from the workers. The creatinine excretion rate observed for these workers is lower than observed in literature. Further, work is in progress to generate a data bank of creatinine excretion rate for most of the workers and also to study the variability in creatinine coefficient for the same individual based on the analysis of samples collected for different duration

Sampling design considerations for demographic studies: a case of colonial seabirds

Science.gov (United States)

Kendall, William L.; Converse, Sarah J.; Doherty, Paul F.; Naughton, Maura B.; Anders, Angela; Hines, James E.; Flint, Elizabeth

2009-01-01

For the purposes of making many informed conservation decisions, the main goal for data collection is to assess population status and allow prediction of the consequences of candidate management actions. Reducing the bias and variance of estimates of population parameters reduces uncertainty in population status and projections, thereby reducing the overall uncertainty under which a population manager must make a decision. In capture-recapture studies, imperfect detection of individuals, unobservable life-history states, local movement outside study areas, and tag loss can cause bias or precision problems with estimates of population parameters. Furthermore, excessive disturbance to individuals during capture?recapture sampling may be of concern because disturbance may have demographic consequences. We address these problems using as an example a monitoring program for Black-footed Albatross (Phoebastria nigripes) and Laysan Albatross (Phoebastria immutabilis) nesting populations in the northwestern Hawaiian Islands. To mitigate these estimation problems, we describe a synergistic combination of sampling design and modeling approaches. Solutions include multiple capture periods per season and multistate, robust design statistical models, dead recoveries and incidental observations, telemetry and data loggers, buffer areas around study plots to neutralize the effect of local movements outside study plots, and double banding and statistical models that account for band loss. We also present a variation on the robust capture?recapture design and a corresponding statistical model that minimizes disturbance to individuals. For the albatross case study, this less invasive robust design was more time efficient and, when used in combination with a traditional robust design, reduced the standard error of detection probability by 14% with only two hours of additional effort in the field. These field techniques and associated modeling approaches are applicable to studies of

Comparison of Four Estimators under sampling without Replacement

African Journals Online (AJOL)

The results were obtained using a program written in Microsoft Visual C++ programming language. It was observed that the two-stage sampling under unequal probabilities without replacement is always better than the other three estimators considered. Keywords: Unequal probability sampling, two-stage sampling, ...

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

Science.gov (United States)

Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

2014-12-19

In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different

Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

OpenAIRE

Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

2016-01-01

The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic ...

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Science.gov (United States)

Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-01-01

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

Science.gov (United States)

Debasish Saha; Armen R. Kemanian; Benjamin M. Rau; Paul R. Adler; Felipe Montes

2017-01-01

Annual cumulative soil nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. We used outputs from simulations obtained with an agroecosystem model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2O fluxes were simulated for Ames, IA (...

Sample size methods for estimating HIV incidence from cross-sectional surveys.

Science.gov (United States)

Konikoff, Jacob; Brookmeyer, Ron

2015-12-01

Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this article, we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this article at the Biometrics website on Wiley Online Library. © 2015, The International Biometric Society.

Estimating fluvial wood discharge from timelapse photography with varying sampling intervals

Science.gov (United States)

Anderson, N. K.

2013-12-01

There is recent focus on calculating wood budgets for streams and rivers to help inform management decisions, ecological studies and carbon/nutrient cycling models. Most work has measured in situ wood in temporary storage along stream banks or estimated wood inputs from banks. Little effort has been employed monitoring and quantifying wood in transport during high flows. This paper outlines a procedure for estimating total seasonal wood loads using non-continuous coarse interval sampling and examines differences in estimation between sampling at 1, 5, 10 and 15 minutes. Analysis is performed on wood transport for the Slave River in Northwest Territories, Canada. Relative to the 1 minute dataset, precision decreased by 23%, 46% and 60% for the 5, 10 and 15 minute datasets, respectively. Five and 10 minute sampling intervals provided unbiased equal variance estimates of 1 minute sampling, whereas 15 minute intervals were biased towards underestimation by 6%. Stratifying estimates by day and by discharge increased precision over non-stratification by 4% and 3%, respectively. Not including wood transported during ice break-up, the total minimum wood load estimated at this site is 3300 × 800$ m3 for the 2012 runoff season. The vast majority of the imprecision in total wood volumes came from variance in estimating average volume per log. Comparison of proportions and variance across sample intervals using bootstrap sampling to achieve equal n. Each trial was sampled for n=100, 10,000 times and averaged. All trials were then averaged to obtain an estimate for each sample interval. Dashed lines represent values from the one minute dataset.

Optimal design criteria - prediction vs. parameter estimation

Science.gov (United States)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Effects of systematic sampling on satellite estimates of deforestation rates

International Nuclear Information System (INIS)

Steininger, M K; Godoy, F; Harper, G

2009-01-01

Options for satellite monitoring of deforestation rates over large areas include the use of sampling. Sampling may reduce the cost of monitoring but is also a source of error in estimates of areas and rates. A common sampling approach is systematic sampling, in which sample units of a constant size are distributed in some regular manner, such as a grid. The proposed approach for the 2010 Forest Resources Assessment (FRA) of the UN Food and Agriculture Organization (FAO) is a systematic sample of 10 km wide squares at every 1 deg. intersection of latitude and longitude. We assessed the outcome of this and other systematic samples for estimating deforestation at national, sub-national and continental levels. The study is based on digital data on deforestation patterns for the five Amazonian countries outside Brazil plus the Brazilian Amazon. We tested these schemes by varying sample-unit size and frequency. We calculated two estimates of sampling error. First we calculated the standard errors, based on the size, variance and covariance of the samples, and from this calculated the 95% confidence intervals (CI). Second, we calculated the actual errors, based on the difference between the sample-based estimates and the estimates from the full-coverage maps. At the continental level, the 1 deg., 10 km scheme had a CI of 21% and an actual error of 8%. At the national level, this scheme had CIs of 126% for Ecuador and up to 67% for other countries. At this level, increasing sampling density to every 0.25 deg. produced a CI of 32% for Ecuador and CIs of up to 25% for other countries, with only Brazil having a CI of less than 10%. Actual errors were within the limits of the CIs in all but two of the 56 cases. Actual errors were half or less of the CIs in all but eight of these cases. These results indicate that the FRA 2010 should have CIs of smaller than or close to 10% at the continental level. However, systematic sampling at the national level yields large CIs unless the

Design of a New Concentration Series for the Orthogonal Sample Design Approach and Estimation of the Number of Reactions in Chemical Systems.

Science.gov (United States)

Shi, Jiajia; Liu, Yuhai; Guo, Ran; Li, Xiaopei; He, Anqi; Gao, Yunlong; Wei, Yongju; Liu, Cuige; Zhao, Ying; Xu, Yizhuang; Noda, Isao; Wu, Jinguang

2015-11-01

A new concentration series is proposed for the construction of a two-dimensional (2D) synchronous spectrum for orthogonal sample design analysis to probe intermolecular interaction between solutes dissolved in the same solutions. The obtained 2D synchronous spectrum possesses the following two properties: (1) cross peaks in the 2D synchronous spectra can be used to reflect intermolecular interaction reliably, since interference portions that have nothing to do with intermolecular interaction are completely removed, and (2) the two-dimensional synchronous spectrum produced can effectively avoid accidental collinearity. Hence, the correct number of nonzero eigenvalues can be obtained so that the number of chemical reactions can be estimated. In a real chemical system, noise present in one-dimensional spectra may also produce nonzero eigenvalues. To get the correct number of chemical reactions, we classified nonzero eigenvalues into significant nonzero eigenvalues and insignificant nonzero eigenvalues. Significant nonzero eigenvalues can be identified by inspecting the pattern of the corresponding eigenvector with help of the Durbin-Watson statistic. As a result, the correct number of chemical reactions can be obtained from significant nonzero eigenvalues. This approach provides a solid basis to obtain insight into subtle spectral variations caused by intermolecular interaction.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus Using Unstructured Sampling Data.

Directory of Open Access Journals (Sweden)

Femke Broekhuis

Full Text Available Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

Science.gov (United States)

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Quality-control design for surface-water sampling in the National Water-Quality Network

Science.gov (United States)

Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

2018-04-10

The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

Science.gov (United States)

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new fractionator principle with varying sampling fractions: exemplified by estimation of synapse number using electron microscopy

DEFF Research Database (Denmark)

Witgen, Brent Marvin; Grady, M. Sean; Nyengaard, Jens Randel

2006-01-01

The quantification of ultrastructure has been permanently improved by the application of new stereological principles. Both precision and efficiency have been enhanced. Here we report for the first time a fractionator method that can be applied at the electron microscopy level. This new design...... the total object number using section sampling fractions based on the average thickness of sections of variable thicknesses. As an alternative, this approach estimates the correct particle section sampling probability based on an estimator of the Horvitz-Thompson type, resulting in a theoretically more...

Adaptive OFDM Radar Waveform Design for Improved Micro-Doppler Estimation

Energy Technology Data Exchange (ETDEWEB)

Sen, Satyabrata [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Engineering Science Advanced Research, Computer Science and Mathematics Division

2014-07-01

Here we analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a rotating target having multiple scattering centers. The use of a frequency-diverse OFDM signal enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. We characterize the accuracy of micro-Doppler frequency estimation by computing the Cramer-Rao bound (CRB) on the angular-velocity estimate of the target. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations with respect to the signal-to-noise ratios, number of temporal samples, and number of OFDM subcarriers. We also analysed numerically the improvement in estimation accuracy due to the adaptive waveform design. A grid-based maximum likelihood estimation technique is applied to evaluate the corresponding mean-squared error performance.

A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem

KAUST Repository

Delaigle, Aurore

2009-03-01

Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.

Estimating abundance of mountain lions from unstructured spatial sampling

Science.gov (United States)

Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; Mckelvey, Kevin S.

2012-01-01

Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km2 (95% Cl 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% Cl 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and

An alternative procedure for estimating the population mean in simple random sampling

Directory of Open Access Journals (Sweden)

Housila P. Singh

2012-03-01

Full Text Available This paper deals with the problem of estimating the finite population mean using auxiliary information in simple random sampling. Firstly we have suggested a correction to the mean squared error of the estimator proposed by Gupta and Shabbir [On improvement in estimating the population mean in simple random sampling. Jour. Appl. Statist. 35(5 (2008, pp. 559-566]. Later we have proposed a ratio type estimator and its properties are studied in simple random sampling. Numerically we have shown that the proposed class of estimators is more efficient than different known estimators including Gupta and Shabbir (2008 estimator.

Reef-associated crustacean fauna: biodiversity estimates using semi-quantitative sampling and DNA barcoding

Science.gov (United States)

Plaisance, L.; Knowlton, N.; Paulay, G.; Meyer, C.

2009-12-01

The cryptofauna associated with coral reefs accounts for a major part of the biodiversity in these ecosystems but has been largely overlooked in biodiversity estimates because the organisms are hard to collect and identify. We combine a semi-quantitative sampling design and a DNA barcoding approach to provide metrics for the diversity of reef-associated crustacean. Twenty-two similar-sized dead heads of Pocillopora were sampled at 10 m depth from five central Pacific Ocean localities (four atolls in the Northern Line Islands and in Moorea, French Polynesia). All crustaceans were removed, and partial cytochrome oxidase subunit I was sequenced from 403 individuals, yielding 135 distinct taxa using a species-level criterion of 5% similarity. Most crustacean species were rare; 44% of the OTUs were represented by a single individual, and an additional 33% were represented by several specimens found only in one of the five localities. The Northern Line Islands and Moorea shared only 11 OTUs. Total numbers estimated by species richness statistics (Chao1 and ACE) suggest at least 90 species of crustaceans in Moorea and 150 in the Northern Line Islands for this habitat type. However, rarefaction curves for each region failed to approach an asymptote, and Chao1 and ACE estimators did not stabilize after sampling eight heads in Moorea, so even these diversity figures are underestimates. Nevertheless, even this modest sampling effort from a very limited habitat resulted in surprisingly high species numbers.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

Directory of Open Access Journals (Sweden)

Manan Gupta

Full Text Available Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates

Comparison of sampling techniques for Bayesian parameter estimation

Science.gov (United States)

Allison, Rupert; Dunkley, Joanna

2014-02-01

The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

Small sample GEE estimation of regression parameters for longitudinal data.

Science.gov (United States)

Paul, Sudhir; Zhang, Xuemao

2014-09-28

Longitudinal (clustered) response data arise in many bio-statistical applications which, in general, cannot be assumed to be independent. Generalized estimating equation (GEE) is a widely used method to estimate marginal regression parameters for correlated responses. The advantage of the GEE is that the estimates of the regression parameters are asymptotically unbiased even if the correlation structure is misspecified, although their small sample properties are not known. In this paper, two bias adjusted GEE estimators of the regression parameters in longitudinal data are obtained when the number of subjects is small. One is based on a bias correction, and the other is based on a bias reduction. Simulations show that the performances of both the bias-corrected methods are similar in terms of bias, efficiency, coverage probability, average coverage length, impact of misspecification of correlation structure, and impact of cluster size on bias correction. Both these methods show superior properties over the GEE estimates for small samples. Further, analysis of data involving a small number of subjects also shows improvement in bias, MSE, standard error, and length of the confidence interval of the estimates by the two bias adjusted methods over the GEE estimates. For small to moderate sample sizes (N ≤50), either of the bias-corrected methods GEEBc and GEEBr can be used. However, the method GEEBc should be preferred over GEEBr, as the former is computationally easier. For large sample sizes, the GEE method can be used. Copyright © 2014 John Wiley & Sons, Ltd.

Bayesian Simultaneous Estimation for Means in k Sample Problems

OpenAIRE

Imai, Ryo; Kubokawa, Tatsuya; Ghosh, Malay

2017-01-01

This paper is concerned with the simultaneous estimation of k population means when one suspects that the k means are nearly equal. As an alternative to the preliminary test estimator based on the test statistics for testing hypothesis of equal means, we derive Bayesian and minimax estimators which shrink individual sample means toward a pooled mean estimator given under the hypothesis. Interestingly, it is shown that both the preliminary test estimator and the Bayesian minimax shrinkage esti...

Turbidity-controlled sampling for suspended sediment load estimation

Science.gov (United States)

Jack Lewis

2003-01-01

Abstract - Automated data collection is essential to effectively measure suspended sediment loads in storm events, particularly in small basins. Continuous turbidity measurements can be used, along with discharge, in an automated system that makes real-time sampling decisions to facilitate sediment load estimation. The Turbidity Threshold Sampling method distributes...

Evaluation of optimized bronchoalveolar lavage sampling designs for characterization of pulmonary drug distribution.

Science.gov (United States)

Clewe, Oskar; Karlsson, Mats O; Simonsson, Ulrika S H

2015-12-01

Bronchoalveolar lavage (BAL) is a pulmonary sampling technique for characterization of drug concentrations in epithelial lining fluid and alveolar cells. Two hypothetical drugs with different pulmonary distribution rates (fast and slow) were considered. An optimized BAL sampling design was generated assuming no previous information regarding the pulmonary distribution (rate and extent) and with a maximum of two samples per subject. Simulations were performed to evaluate the impact of the number of samples per subject (1 or 2) and the sample size on the relative bias and relative root mean square error of the parameter estimates (rate and extent of pulmonary distribution). The optimized BAL sampling design depends on a characterized plasma concentration time profile, a population plasma pharmacokinetic model, the limit of quantification (LOQ) of the BAL method and involves only two BAL sample time points, one early and one late. The early sample should be taken as early as possible, where concentrations in the BAL fluid ≥ LOQ. The second sample should be taken at a time point in the declining part of the plasma curve, where the plasma concentration is equivalent to the plasma concentration in the early sample. Using a previously described general pulmonary distribution model linked to a plasma population pharmacokinetic model, simulated data using the final BAL sampling design enabled characterization of both the rate and extent of pulmonary distribution. The optimized BAL sampling design enables characterization of both the rate and extent of the pulmonary distribution for both fast and slowly equilibrating drugs.

Design unbiased estimation in line intersect sampling using segmented transects

Science.gov (United States)

David L.R. Affleck; Timothy G. Gregoire; Harry T. Valentine; Harry T. Valentine

2005-01-01

In many applications of line intersect sampling. transects consist of multiple, connected segments in a prescribed configuration. The relationship between the transect configuration and the selection probability of a population element is illustrated and a consistent sampling protocol, applicable to populations composed of arbitrarily shaped elements, is proposed. It...

Estimating mean change in population salt intake using spot urine samples.

Science.gov (United States)

Petersen, Kristina S; Wu, Jason H Y; Webster, Jacqui; Grimes, Carley; Woodward, Mark; Nowson, Caryl A; Neal, Bruce

2017-10-01

Spot urine samples are easier to collect than 24-h urine samples and have been used with estimating equations to derive the mean daily salt intake of a population. Whether equations using data from spot urine samples can also be used to estimate change in mean daily population salt intake over time is unknown. We compared estimates of change in mean daily population salt intake based upon 24-h urine collections with estimates derived using equations based on spot urine samples. Paired and unpaired 24-h urine samples and spot urine samples were collected from individuals in two Australian populations, in 2011 and 2014. Estimates of change in daily mean population salt intake between 2011 and 2014 were obtained directly from the 24-h urine samples and by applying established estimating equations (Kawasaki, Tanaka, Mage, Toft, INTERSALT) to the data from spot urine samples. Differences between 2011 and 2014 were calculated using mixed models. A total of 1000 participants provided a 24-h urine sample and a spot urine sample in 2011, and 1012 did so in 2014 (paired samples n = 870; unpaired samples n = 1142). The participants were community-dwelling individuals living in the State of Victoria or the town of Lithgow in the State of New South Wales, Australia, with a mean age of 55 years in 2011. The mean (95% confidence interval) difference in population salt intake between 2011 and 2014 determined from the 24-h urine samples was -0.48g/day (-0.74 to -0.21; P spot urine samples was -0.24 g/day (-0.42 to -0.06; P = 0.01) using the Tanaka equation, -0.42 g/day (-0.70 to -0.13; p = 0.004) using the Kawasaki equation, -0.51 g/day (-1.00 to -0.01; P = 0.046) using the Mage equation, -0.26 g/day (-0.42 to -0.10; P = 0.001) using the Toft equation, -0.20 g/day (-0.32 to -0.09; P = 0.001) using the INTERSALT equation and -0.27 g/day (-0.39 to -0.15; P  0.058). Separate analysis of the unpaired and paired data showed that detection of

Effects of sampling conditions on DNA-based estimates of American black bear abundance

Science.gov (United States)

Laufenberg, Jared S.; Van Manen, Frank T.; Clark, Joseph D.

2013-01-01

DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear (Ursus americanus) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (pA and pB, respectively, or p, collectively), the proportion of each mixture (π), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI = 114–272) and 100 (95% CI = 74–167), respectively (pooled N = 261, 95% CI = 192–419), and the average weekly p was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation ≤20%) of estimates using logistic regression. The capture probability

Estimating waste disposal quantities from raw waste samples

International Nuclear Information System (INIS)

Negin, C.A.; Urland, C.S.; Hitz, C.G.; GPU Nuclear Corp., Middletown, PA)

1985-01-01

Estimating the disposal quantity of waste resulting from stabilization of radioactive sludge is complex because of the many factors relating to sample analysis results, radioactive decay, allowable disposal concentrations, and options for disposal containers. To facilitate this estimation, a microcomputer spread sheet template was created. The spread sheet has saved considerable engineering hours. 1 fig., 3 tabs

Iterative importance sampling algorithms for parameter estimation

OpenAIRE

Morzfeld, Matthias; Day, Marcus S.; Grout, Ray W.; Pau, George Shu Heng; Finsterle, Stefan A.; Bell, John B.

2016-01-01

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov Chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is ...

Monitoring oil persistence on beaches : SCAT versus stratified random sampling designs

International Nuclear Information System (INIS)

Short, J.W.; Lindeberg, M.R.; Harris, P.M.; Maselko, J.M.; Pella, J.J.; Rice, S.D.

2003-01-01

In the event of a coastal oil spill, shoreline clean-up assessment teams (SCAT) commonly rely on visual inspection of the entire affected area to monitor the persistence of the oil on beaches. Occasionally, pits are excavated to evaluate the persistence of subsurface oil. This approach is practical for directing clean-up efforts directly following a spill. However, sampling of the 1989 Exxon Valdez oil spill in Prince William Sound 12 years later has shown that visual inspection combined with pit excavation does not offer estimates of contaminated beach area of stranded oil volumes. This information is needed to statistically evaluate the significance of change with time. Assumptions regarding the correlation of visually-evident surface oil and cryptic subsurface oil are usually not evaluated as part of the SCAT mandate. Stratified random sampling can avoid such problems and could produce precise estimates of oiled area and volume that allow for statistical assessment of major temporal trends and the extent of the impact. The 2001 sampling of the shoreline of Prince William Sound showed that 15 per cent of surface oil occurrences were associated with subsurface oil. This study demonstrates the usefulness of the stratified random sampling method and shows how sampling design parameters impact statistical outcome. Power analysis based on the study results, indicate that optimum power is derived when unnecessary stratification is avoided. It was emphasized that sampling effort should be balanced between choosing sufficient beaches for sampling and the intensity of sampling

Sampling strategies for estimating brook trout effective population size

Science.gov (United States)

Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher

2012-01-01

The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

Energy Technology Data Exchange (ETDEWEB)

Price, Oliver R., E-mail: oliver.price@unilever.co [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Oliver, Margaret A. [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom); Walker, Allan [Warwick-HRI, University of Warwick, Wellesbourne, Warwick, CV32 6EF (United Kingdom); Wood, Martin [University of Reading, Soil Science Department, Whiteknights, Reading, RG6 6UR (United Kingdom)

2009-05-15

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

International Nuclear Information System (INIS)

Price, Oliver R.; Oliver, Margaret A.; Walker, Allan; Wood, Martin

2009-01-01

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field. - Estimating the spatial scale of herbicide and soil interactions by nested sampling.

Genotyping faecal samples of Bengal tiger Panthera tigris tigris for population estimation: A pilot study

Directory of Open Access Journals (Sweden)

Singh Lalji

2006-10-01

Full Text Available Abstract Background Bengal tiger Panthera tigris tigris the National Animal of India, is an endangered species. Estimating populations for such species is the main objective for designing conservation measures and for evaluating those that are already in place. Due to the tiger's cryptic and secretive behaviour, it is not possible to enumerate and monitor its populations through direct observations; instead indirect methods have always been used for studying tigers in the wild. DNA methods based on non-invasive sampling have not been attempted so far for tiger population studies in India. We describe here a pilot study using DNA extracted from faecal samples of tigers for the purpose of population estimation. Results In this study, PCR primers were developed based on tiger-specific variations in the mitochondrial cytochrome b for reliably identifying tiger faecal samples from those of sympatric carnivores. Microsatellite markers were developed for the identification of individual tigers with a sibling Probability of Identity of 0.005 that can distinguish even closely related individuals with 99.9% certainty. The effectiveness of using field-collected tiger faecal samples for DNA analysis was evaluated by sampling, identification and subsequently genotyping samples from two protected areas in southern India. Conclusion Our results demonstrate the feasibility of using tiger faecal matter as a potential source of DNA for population estimation of tigers in protected areas in India in addition to the methods currently in use.

Estimating population salt intake in India using spot urine samples.

Science.gov (United States)

Petersen, Kristina S; Johnson, Claire; Mohan, Sailesh; Rogers, Kris; Shivashankar, Roopa; Thout, Sudhir Raj; Gupta, Priti; He, Feng J; MacGregor, Graham A; Webster, Jacqui; Santos, Joseph Alvin; Krishnan, Anand; Maulik, Pallab K; Reddy, K Srinath; Gupta, Ruby; Prabhakaran, Dorairaj; Neal, Bruce

2017-11-01

To compare estimates of mean population salt intake in North and South India derived from spot urine samples versus 24-h urine collections. In a cross-sectional survey, participants were sampled from slum, urban and rural communities in North and in South India. Participants provided 24-h urine collections, and random morning spot urine samples. Salt intake was estimated from the spot urine samples using a series of established estimating equations. Salt intake data from the 24-h urine collections and spot urine equations were weighted to provide estimates of salt intake for Delhi and Haryana, and Andhra Pradesh. A total of 957 individuals provided a complete 24-h urine collection and a spot urine sample. Weighted mean salt intake based on the 24-h urine collection, was 8.59 (95% confidence interval 7.73-9.45) and 9.46 g/day (8.95-9.96) in Delhi and Haryana, and Andhra Pradesh, respectively. Corresponding estimates based on the Tanaka equation [9.04 (8.63-9.45) and 9.79 g/day (9.62-9.96) for Delhi and Haryana, and Andhra Pradesh, respectively], the Mage equation [8.80 (7.67-9.94) and 10.19 g/day (95% CI 9.59-10.79)], the INTERSALT equation [7.99 (7.61-8.37) and 8.64 g/day (8.04-9.23)] and the INTERSALT equation with potassium [8.13 (7.74-8.52) and 8.81 g/day (8.16-9.46)] were all within 1 g/day of the estimate based upon 24-h collections. For the Toft equation, estimates were 1-2 g/day higher [9.94 (9.24-10.64) and 10.69 g/day (9.44-11.93)] and for the Kawasaki equation they were 3-4 g/day higher [12.14 (11.30-12.97) and 13.64 g/day (13.15-14.12)]. In urban and rural areas in North and South India, most spot urine-based equations provided reasonable estimates of mean population salt intake. Equations that did not provide good estimates may have failed because specimen collection was not aligned with the original method.

Heat experiment design to estimate temperature dependent thermal properties

International Nuclear Information System (INIS)

Romanovski, M

2008-01-01

Experimental conditions are studied to optimize transient experiments for estimating temperature dependent thermal conductivity and volumetric heat capacity. A mathematical model of a specimen is the one-dimensional heat equation with boundary conditions of the second kind. Thermal properties are assumed to vary nonlinearly with temperature. Experimental conditions refer to the thermal loading scheme, sampling times and sensor location. A numerical model of experimental configurations is studied to elicit the optimal conditions. The numerical solution of the design problem is formulated on a regularization scheme with a stabilizer minimization without a regularization parameter. An explicit design criterion is used to reveal the optimal sensor location, heating duration and flux magnitude. Results obtained indicate that even the strongly nonlinear experimental design problem admits the aggregation of its solution and has a strictly defined optimal measurement scheme. Additional region of temperature measurements with allowable identification error is revealed.

Networked Estimation for Event-Based Sampling Systems with Packet Dropouts

Directory of Open Access Journals (Sweden)

Young Soo Suh

2009-04-01

Full Text Available This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen.

Comparison of distance sampling estimates to a known population ...

African Journals Online (AJOL)

Line-transect sampling was used to obtain abundance estimates of an Ant-eating Chat Myrmecocichla formicivora population to compare these with the true size of the population. The population size was determined by a long-term banding study, and abundance estimates were obtained by surveying line transects.

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

Sample design effects in landscape genetics

Science.gov (United States)

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F.; Amidan, Brett G.; Matzke, Brett D.

2009-02-16

This report describes the experimental and sampling design developed to assess sampling approaches and methods for detecting contamination in a building and clearing the building for use after decontamination. An Idaho National Laboratory (INL) building will be contaminated with BG (Bacillus globigii, renamed Bacillus atrophaeus), a simulant for Bacillus anthracis (BA). The contamination, sampling, decontamination, and re-sampling will occur per the experimental and sampling design. This INL-2 Sample Collection Operational Test is being planned by the Validated Sampling Plan Working Group (VSPWG). The primary objectives are: 1) Evaluate judgmental and probabilistic sampling for characterization as well as probabilistic and combined (judgment and probabilistic) sampling approaches for clearance, 2) Conduct these evaluations for gradient contamination (from low or moderate down to absent or undetectable) for different initial concentrations of the contaminant, 3) Explore judgment composite sampling approaches to reduce sample numbers, 4) Collect baseline data to serve as an indication of the actual levels of contamination in the tests. A combined judgmental and random (CJR) approach uses Bayesian methodology to combine judgmental and probabilistic samples to make clearance statements of the form "X% confidence that at least Y% of an area does not contain detectable contamination” (X%/Y% clearance statements). The INL-2 experimental design has five test events, which 1) vary the floor of the INL building on which the contaminant will be released, 2) provide for varying the amount of contaminant released to obtain desired concentration gradients, and 3) investigate overt as well as covert release of contaminants. Desirable contaminant gradients would have moderate to low concentrations of contaminant in rooms near the release point, with concentrations down to zero in other rooms. Such gradients would provide a range of contamination levels to challenge the sampling

Spatially explicit population estimates for black bears based on cluster sampling

Science.gov (United States)

Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

A Sample-Based Forest Monitoring Strategy Using Landsat, AVHRR and MODIS Data to Estimate Gross Forest Cover Loss in Malaysia between 1990 and 2005

Directory of Open Access Journals (Sweden)

Peter Potapov

2013-04-01

Full Text Available Insular Southeast Asia is a hotspot of humid tropical forest cover loss. A sample-based monitoring approach quantifying forest cover loss from Landsat imagery was implemented to estimate gross forest cover loss for two eras, 1990–2000 and 2000–2005. For each time interval, a probability sample of 18.5 km × 18.5 km blocks was selected, and pairs of Landsat images acquired per sample block were interpreted to quantify forest cover area and gross forest cover loss. Stratified random sampling was implemented for 2000–2005 with MODIS-derived forest cover loss used to define the strata. A probability proportional to x (πpx design was implemented for 1990–2000 with AVHRR-derived forest cover loss used as the x variable to increase the likelihood of including forest loss area in the sample. The estimated annual gross forest cover loss for Malaysia was 0.43 Mha/yr (SE = 0.04 during 1990–2000 and 0.64 Mha/yr (SE = 0.055 during 2000–2005. Our use of the πpx sampling design represents a first practical trial of this design for sampling satellite imagery. Although the design performed adequately in this study, a thorough comparative investigation of the πpx design relative to other sampling strategies is needed before general design recommendations can be put forth.

Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach

KAUST Repository

Ballal, Tarig

2014-01-01

This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. These observations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity, the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling scheme was tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in most cases; while in the high SNR regime, it also outperforms the LMMSE estimator. © 2014 IEEE.

The use of Thompson sampling to increase estimation precision

NARCIS (Netherlands)

Kaptein, M.C.

2015-01-01

In this article, we consider a sequential sampling scheme for efficient estimation of the difference between the means of two independent treatments when the population variances are unequal across groups. The sampling scheme proposed is based on a solution to bandit problems called Thompson

Estimating Sample Size for Usability Testing

Directory of Open Access Journals (Sweden)

Alex Cazañas

2017-02-01

Full Text Available One strategy used to assure that an interface meets user requirements is to conduct usability testing. When conducting such testing one of the unknowns is sample size. Since extensive testing is costly, minimizing the number of participants can contribute greatly to successful resource management of a project. Even though a significant number of models have been proposed to estimate sample size in usability testing, there is still not consensus on the optimal size. Several studies claim that 3 to 5 users suffice to uncover 80% of problems in a software interface. However, many other studies challenge this assertion. This study analyzed data collected from the user testing of a web application to verify the rule of thumb, commonly known as the “magic number 5”. The outcomes of the analysis showed that the 5-user rule significantly underestimates the required sample size to achieve reasonable levels of problem detection.

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

Science.gov (United States)

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Density meter algorithm and system for estimating sampling/mixing uncertainty

International Nuclear Information System (INIS)

Shine, E.P.

1986-01-01

The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statistical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses

Density meter algorithm and system for estimating sampling/mixing uncertainty

International Nuclear Information System (INIS)

Shine, E.P.

1986-01-01

The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statisical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

Directory of Open Access Journals (Sweden)

Lauren Hund

Full Text Available Lot quality assurance sampling (LQAS surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

Science.gov (United States)

Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration

DEFF Research Database (Denmark)

Nielsen, Morten Ø.; Frederiksen, Per Houmann

2005-01-01

In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The es...... the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased.......In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods....... The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all...

30 CFR 71.208 - Bimonthly sampling; designated work positions.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Bimonthly sampling; designated work positions... UNDERGROUND COAL MINES Sampling Procedures § 71.208 Bimonthly sampling; designated work positions. (a) Each... standard when quartz is present), respirable dust sampling of designated work positions shall begin on the...

Estimation methods with ordered exposure subject to measurement error and missingness in semi-ecological design

Directory of Open Access Journals (Sweden)

Kim Hyang-Mi

2012-09-01

Full Text Available Abstract Background In epidemiological studies, it is often not possible to measure accurately exposures of participants even if their response variable can be measured without error. When there are several groups of subjects, occupational epidemiologists employ group-based strategy (GBS for exposure assessment to reduce bias due to measurement errors: individuals of a group/job within study sample are assigned commonly to the sample mean of exposure measurements from their group in evaluating the effect of exposure on the response. Therefore, exposure is estimated on an ecological level while health outcomes are ascertained for each subject. Such study design leads to negligible bias in risk estimates when group means are estimated from ‘large’ samples. However, in many cases, only a small number of observations are available to estimate the group means, and this causes bias in the observed exposure-disease association. Also, the analysis in a semi-ecological design may involve exposure data with the majority missing and the rest observed with measurement errors and complete response data collected with ascertainment. Methods In workplaces groups/jobs are naturally ordered and this could be incorporated in estimation procedure by constrained estimation methods together with the expectation and maximization (EM algorithms for regression models having measurement error and missing values. Four methods were compared by a simulation study: naive complete-case analysis, GBS, the constrained GBS (CGBS, and the constrained expectation and maximization (CEM. We illustrated the methods in the analysis of decline in lung function due to exposures to carbon black. Results Naive and GBS approaches were shown to be inadequate when the number of exposure measurements is too small to accurately estimate group means. The CEM method appears to be best among them when within each exposure group at least a ’moderate’ number of individuals have their

Assessment of sampling strategies for estimation of site mean concentrations of stormwater pollutants.

Science.gov (United States)

McCarthy, David T; Zhang, Kefeng; Westerlund, Camilla; Viklander, Maria; Bertrand-Krajewski, Jean-Luc; Fletcher, Tim D; Deletic, Ana

2018-02-01

The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective sampling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective sampling strategies. Results indicate that the random sampling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli. The differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and E. coli), indicating that there is little benefit in investing in collection of more than one sample per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R 2  = 0.49; P sampling frequency needed to accurately estimate SMCs of pollutants. Crown

Optimum sample size to estimate mean parasite abundance in fish parasite surveys

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Shvydka S.

2018-03-01

Full Text Available To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI was based on the Bag of Little Bootstraps (BLB. The abundance of two species of monogenean parasites Ligophorus cephali and L. mediterraneus from Mugil cephalus across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i based on CIs width a reasonable precision level for the mean abundance in parasitological surveys of Ligophorus spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the CIs width, and ii the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.

Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

Directory of Open Access Journals (Sweden)

Wang Yanqing

2014-04-01

Full Text Available During environment testing, the estimation of random vibration signals (RVS is an important technique for the airborne platform safety and reliability. However, the available methods including extreme value envelope method (EVEM, statistical tolerances method (STM and improved statistical tolerance method (ISTM require large samples and typical probability distribution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method (GBM is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated interval, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method (BM and gray method (GM in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.

Estimation of uranium in bioassay samples of occupational workers by laser fluorimetry

International Nuclear Information System (INIS)

Suja, A.; Prabhu, S.P.; Sawant, P.D.; Sarkar, P.K.; Tiwari, A.K.; Sharma, R.

2010-01-01

A newly established uranium processing facility has been commissioned at BARC, Trombay. Monitoring of occupational workers at regulars intervals is essential to assess intake of uranium by the workers in this facility. The design and engineering safety features of the plant are such that there is very low probability of uranium getting air borne during normal operations. However, the leakages from the system during routine maintenance of the plant may result in intake of uranium by workers. As per the new biokinetic model for uranium, 63% of uranium entering the blood stream gets directly excreted in urine. Therefore, bioassay monitoring (urinalysis) was recommended for these workers. A group of 21 workers was selected for bioassay monitoring to assess the existing urinary excretion levels of uranium before the commencement of actual work. For this purpose, sample collection kit along with an instruction slip was provided to the workers. Bioassay samples received were wet ashed with conc. nitric acid and hydrogen peroxide to break down the metabolized complexes of uranium and it was co-precipitated with calcium phosphate. Separation of uranium from the matrix was done using ion exchange technique and final activity quantification in these samples was done using laser fluorimeter (Quantalase, Model No. NFL/02). Calibration of the laser fluorimeter is done using 10 ppb uranium standard (WHO, France Ref. No. 180000). Verification of the system performance is done by measuring concentration of uranium in the standards (1 ppb to 100 ppb). Standard addition method was followed for estimation of uranium concentration in the samples. Uranyl ions present in the sample get excited by pulsed nitrogen laser at 337.1 nm, and on de-excitation emit fluorescence light (540 nm) intensity which is measured by the PMT. To estimate the uranium in the bioassay samples, a known aliquot of the sample was mixed with 5% sodium pyrophosphate and fluorescence intensity was measured

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys

OpenAIRE

Hund, Lauren; Bedrick, Edward J.; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we comp...

Estimating rare events in biochemical systems using conditional sampling

Science.gov (United States)

Sundar, V. S.

2017-01-01

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

Fusion reactor design studies: standard accounts for cost estimates

International Nuclear Information System (INIS)

Schulte, S.C.; Willke, T.L.; Young, J.R.

1978-05-01

The fusion reactor design studies--standard accounts for cost estimates provides a common format from which to assess the economic character of magnetically confined fusion reactor design concepts. The format will aid designers in the preparation of design concept costs estimates and also provide policymakers with a tool to assist in appraising which design concept may be economically promising. The format sets forth a categorization and accounting procedure to be used when estimating fusion reactor busbar energy cost that can be easily and consistently applied. Reasons for developing the procedure, explanations of the procedure, justifications for assumptions made in the procedure, and the applicability of the procedure are described in this document. Adherence to the format when evaluating prospective fusion reactor design concepts will result in the identification of the more promising design concepts thus enabling the fusion power alternatives with better economic potential to be quickly and efficiently developed

Estimation for small domains in double sampling for stratification ...

African Journals Online (AJOL)

In this article, we investigate the effect of randomness of the size of a small domain on the precision of an estimator of mean for the domain under double sampling for stratification. The result shows that for a small domain that cuts across various strata with unknown weights, the sampling variance depends on the within ...

Sampling strategies for efficient estimation of tree foliage biomass

Science.gov (United States)

Hailemariam Temesgen; Vicente Monleon; Aaron Weiskittel; Duncan Wilson

2011-01-01

Conifer crowns can be highly variable both within and between trees, particularly with respect to foliage biomass and leaf area. A variety of sampling schemes have been used to estimate biomass and leaf area at the individual tree and stand scales. Rarely has the effectiveness of these sampling schemes been compared across stands or even across species. In addition,...

Effects of sample size on estimates of population growth rates calculated with matrix models.

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Ian J Fiske

Full Text Available BACKGROUND: Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. METHODOLOGY/PRINCIPAL FINDINGS: Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. CONCLUSIONS/SIGNIFICANCE: We found significant bias at small sample sizes when survival was low (survival = 0.5, and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high

Effects of sample size on estimates of population growth rates calculated with matrix models.

Science.gov (United States)

Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

2008-08-28

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

A method for estimating radioactive cesium concentrations in cattle blood using urine samples.

Science.gov (United States)

Sato, Itaru; Yamagishi, Ryoma; Sasaki, Jun; Satoh, Hiroshi; Miura, Kiyoshi; Kikuchi, Kaoru; Otani, Kumiko; Okada, Keiji

2017-12-01

In the region contaminated by the Fukushima nuclear accident, radioactive contamination of live cattle should be checked before slaughter. In this study, we establish a precise method for estimating radioactive cesium concentrations in cattle blood using urine samples. Blood and urine samples were collected from a total of 71 cattle on two farms in the 'difficult-to-return zone'. Urine 137 Cs, specific gravity, electrical conductivity, pH, sodium, potassium, calcium, and creatinine were measured and various estimation methods for blood 137 Cs were tested. The average error rate of the estimation was 54.2% without correction. Correcting for urine creatinine, specific gravity, electrical conductivity, or potassium improved the precision of the estimation. Correcting for specific gravity using the following formula gave the most precise estimate (average error rate = 16.9%): [blood 137 Cs] = [urinary 137 Cs]/([specific gravity] - 1)/329. Urine samples are faster to measure than blood samples because urine can be obtained in larger quantities and has a higher 137 Cs concentration than blood. These advantages of urine and the estimation precision demonstrated in our study, indicate that estimation of blood 137 Cs using urine samples is a practical means of monitoring radioactive contamination in live cattle. © 2017 Japanese Society of Animal Science.

Methods for design flood estimation in South Africa | Smithers ...

African Journals Online (AJOL)

The estimation of design floods is necessary for the design of hydraulic structures and to quantify the risk of failure of the structures. Most of the methods used for design flood estimation in South Africa were developed in the late 1960s and early 1970s and are in need of updating with more than 40 years of additional data ...

An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks

International Nuclear Information System (INIS)

Wu, Ji; Zhang, Chenbin; Chen, Zonghai

2016-01-01

Highlights: • An online RUL estimation method for lithium-ion battery is proposed. • RUL is described by the difference among battery terminal voltage curves. • A feed forward neural network is employed for RUL estimation. • Importance sampling is utilized to select feed forward neural network inputs. - Abstract: An accurate battery remaining useful life (RUL) estimation can facilitate the design of a reliable battery system as well as the safety and reliability of actual operation. A reasonable definition and an effective prediction algorithm are indispensable for the achievement of an accurate RUL estimation result. In this paper, the analysis of battery terminal voltage curves under different cycle numbers during charge process is utilized for RUL definition. Moreover, the relationship between RUL and charge curve is simulated by feed forward neural network (FFNN) for its simplicity and effectiveness. Considering the nonlinearity of lithium-ion charge curve, importance sampling (IS) is employed for FFNN input selection. Based on these results, an online approach using FFNN and IS is presented to estimate lithium-ion battery RUL in this paper. Experiments and numerical comparisons are conducted to validate the proposed method. The results show that the FFNN with IS is an accurate estimation method for actual operation.

The Influence of Mark-Recapture Sampling Effort on Estimates of Rock Lobster Survival.

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Ziya Kordjazi

Full Text Available Five annual capture-mark-recapture surveys on Jasus edwardsii were used to evaluate the effect of sample size and fishing effort on the precision of estimated survival probability. Datasets of different numbers of individual lobsters (ranging from 200 to 1,000 lobsters were created by random subsampling from each annual survey. This process of random subsampling was also used to create 12 datasets of different levels of effort based on three levels of the number of traps (15, 30 and 50 traps per day and four levels of the number of sampling-days (2, 4, 6 and 7 days. The most parsimonious Cormack-Jolly-Seber (CJS model for estimating survival probability shifted from a constant model towards sex-dependent models with increasing sample size and effort. A sample of 500 lobsters or 50 traps used on four consecutive sampling-days was required for obtaining precise survival estimations for males and females, separately. Reduced sampling effort of 30 traps over four sampling days was sufficient if a survival estimate for both sexes combined was sufficient for management of the fishery.

The Influence of Mark-Recapture Sampling Effort on Estimates of Rock Lobster Survival

Science.gov (United States)

Kordjazi, Ziya; Frusher, Stewart; Buxton, Colin; Gardner, Caleb; Bird, Tomas

2016-01-01

Five annual capture-mark-recapture surveys on Jasus edwardsii were used to evaluate the effect of sample size and fishing effort on the precision of estimated survival probability. Datasets of different numbers of individual lobsters (ranging from 200 to 1,000 lobsters) were created by random subsampling from each annual survey. This process of random subsampling was also used to create 12 datasets of different levels of effort based on three levels of the number of traps (15, 30 and 50 traps per day) and four levels of the number of sampling-days (2, 4, 6 and 7 days). The most parsimonious Cormack-Jolly-Seber (CJS) model for estimating survival probability shifted from a constant model towards sex-dependent models with increasing sample size and effort. A sample of 500 lobsters or 50 traps used on four consecutive sampling-days was required for obtaining precise survival estimations for males and females, separately. Reduced sampling effort of 30 traps over four sampling days was sufficient if a survival estimate for both sexes combined was sufficient for management of the fishery. PMID:26990561

Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response

Directory of Open Access Journals (Sweden)

Muqaddas Javed

2014-09-01

Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.

Estimation of reference intervals from small samples: an example using canine plasma creatinine.

Science.gov (United States)

Geffré, A; Braun, J P; Trumel, C; Concordet, D

2009-12-01

According to international recommendations, reference intervals should be determined from at least 120 reference individuals, which often are impossible to achieve in veterinary clinical pathology, especially for wild animals. When only a small number of reference subjects is available, the possible bias cannot be known and the normality of the distribution cannot be evaluated. A comparison of reference intervals estimated by different methods could be helpful. The purpose of this study was to compare reference limits determined from a large set of canine plasma creatinine reference values, and large subsets of this data, with estimates obtained from small samples selected randomly. Twenty sets each of 120 and 27 samples were randomly selected from a set of 1439 plasma creatinine results obtained from healthy dogs in another study. Reference intervals for the whole sample and for the large samples were determined by a nonparametric method. The estimated reference limits for the small samples were minimum and maximum, mean +/- 2 SD of native and Box-Cox-transformed values, 2.5th and 97.5th percentiles by a robust method on native and Box-Cox-transformed values, and estimates from diagrams of cumulative distribution functions. The whole sample had a heavily skewed distribution, which approached Gaussian after Box-Cox transformation. The reference limits estimated from small samples were highly variable. The closest estimates to the 1439-result reference interval for 27-result subsamples were obtained by both parametric and robust methods after Box-Cox transformation but were grossly erroneous in some cases. For small samples, it is recommended that all values be reported graphically in a dot plot or histogram and that estimates of the reference limits be compared using different methods.

Inverse sampled Bernoulli (ISB) procedure for estimating a population proportion, with nuclear material applications

International Nuclear Information System (INIS)

Wright, T.

1982-01-01

A new sampling procedure is introduced for estimating a population proportion. The procedure combines the ideas of inverse binomial sampling and Bernoulli sampling. An unbiased estimator is given with its variance. The procedure can be viewed as a generalization of inverse binomial sampling

Modern survey sampling

CERN Document Server

Chaudhuri, Arijit

2014-01-01

Exposure to SamplingAbstract Introduction Concepts of Population, Sample, and SamplingInitial RamificationsAbstract Introduction Sampling Design, Sampling SchemeRandom Numbers and Their Uses in Simple RandomSampling (SRS)Drawing Simple Random Samples with and withoutReplacementEstimation of Mean, Total, Ratio of Totals/Means:Variance and Variance EstimationDetermination of Sample SizesA.2 Appendix to Chapter 2 A.More on Equal Probability Sampling A.Horvitz-Thompson EstimatorA.SufficiencyA.LikelihoodA.Non-Existence Theorem More Intricacies Abstract Introduction Unequal Probability Sampling StrategiesPPS Sampling Exploring Improved WaysAbstract Introduction Stratified Sampling Cluster SamplingMulti-Stage SamplingMulti-Phase Sampling: Ratio and RegressionEstimationviiviii ContentsControlled SamplingModeling Introduction Super-Population ModelingPrediction Approach Model-Assisted Approach Bayesian Methods Spatial SmoothingSampling on Successive Occasions: Panel Rotation Non-Response and Not-at-Homes Weighting Adj...

Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries

Science.gov (United States)

McCormick, Joshua L.; Quist, Michael C.; Schill, Daniel J.

2012-01-01

Roving–roving and roving–access creel surveys are the primary techniques used to obtain information on harvest of Chinook salmon Oncorhynchus tshawytscha in Idaho sport fisheries. Once interviews are conducted using roving–roving or roving–access survey designs, mean catch rate can be estimated with the ratio-of-means (ROM) estimator, the mean-of-ratios (MOR) estimator, or the MOR estimator with exclusion of short-duration (≤0.5 h) trips. Our objective was to examine the relative bias and precision of total catch estimates obtained from use of the two survey designs and three catch rate estimators for Idaho Chinook salmon fisheries. Information on angling populations was obtained by direct visual observation of portions of Chinook salmon fisheries in three Idaho river systems over an 18-d period. Based on data from the angling populations, Monte Carlo simulations were performed to evaluate the properties of the catch rate estimators and survey designs. Among the three estimators, the ROM estimator provided the most accurate and precise estimates of mean catch rate and total catch for both roving–roving and roving–access surveys. On average, the root mean square error of simulated total catch estimates was 1.42 times greater and relative bias was 160.13 times greater for roving–roving surveys than for roving–access surveys. Length-of-stay bias and nonstationary catch rates in roving–roving surveys both appeared to affect catch rate and total catch estimates. Our results suggest that use of the ROM estimator in combination with an estimate of angler effort provided the least biased and most precise estimates of total catch for both survey designs. However, roving–access surveys were more accurate than roving–roving surveys for Chinook salmon fisheries in Idaho.

Estimation of Missing Observations in Two-Level Split-Plot Designs

DEFF Research Database (Denmark)

Almimi, Ashraf A.; Kulahci, Murat; Montgomery, Douglas C.

2008-01-01

Inserting estimates for the missing observations from split-plot designs restores their balanced or orthogonal structure and alleviates the difficulties in the statistical analysis. In this article, we extend a method due to Draper and Stoneman to estimate the missing observations from unreplicated...... two-level factorial and fractional factorial split-plot (FSP and FFSP) designs. The missing observations, which can either be from the same whole plot, from different whole plots, or comprise entire whole plots, are estimated by equating to zero a number of specific contrast columns equal...... to the number of the missing observations. These estimates are inserted into the design table and the estimates for the remaining effects (or alias chains of effects as the case with FFSP designs) are plotted on two half-normal plots: one for the whole-plot effects and the other for the subplot effects...

A test of alternative estimators for volume at time 1 from remeasured point samples

Science.gov (United States)

Francis A. Roesch; Edwin J. Green; Charles T. Scott

1993-01-01

Two estimators for volume at time 1 for use with permanent horizontal point samples are evaluated. One estimator, used traditionally, uses only the trees sampled at time 1, while the second estimator, originally presented by Roesch and coauthors (F.A. Roesch, Jr., E.J. Green, and C.T. Scott. 1989. For. Sci. 35(2):281-293). takes advantage of additional sample...

Turbidity-controlled suspended sediment sampling for runoff-event load estimation

Science.gov (United States)

Jack Lewis

1996-01-01

Abstract - For estimating suspended sediment concentration (SSC) in rivers, turbidity is generally a much better predictor than water discharge. Although it is now possible to collect continuous turbidity data even at remote sites, sediment sampling and load estimation are still conventionally based on discharge. With frequent calibration the relation of turbidity to...

Performance of sampling methods to estimate log characteristics for wildlife.

Science.gov (United States)

Lisa J. Bate; Torolf R. Torgersen; Michael J. Wisdom; Edward O. Garton

2004-01-01

Accurate estimation of the characteristics of log resources, or coarse woody debris (CWD), is critical to effective management of wildlife and other forest resources. Despite the importance of logs as wildlife habitat, methods for sampling logs have traditionally focused on silvicultural and fire applications. These applications have emphasized estimates of log volume...

MANTEL-HAENSZEL TYPE ESTIMATORS FOR THE COUNTER-MATCHED SAMPLING DESIGN IN NESTED CASE-CONTROL STUDY

OpenAIRE

Fujii, Yoshinori; Zhang, Zhong-Zhan; 藤井, 良宜

2001-01-01

We are concerned with a counter-matched nested case-control study. Assuming the proportional hazards model, the Mantel-Haenszel estimators of hazard rates are presented in two situations. The proposed estimators can be calculated without estimating the nuisance parameter. Consistent estimators of the variance of the proposed hazard rate estimators are also developed. We compare these estimators to the maximum partial likelihood estimators in the asymptotic variance. The methods are illustrate...

Estimation of Sensitive Proportion by Randomized Response Data in Successive Sampling

Directory of Open Access Journals (Sweden)

Bo Yu

2015-01-01

Full Text Available This paper considers the problem of estimation for binomial proportions of sensitive or stigmatizing attributes in the population of interest. Randomized response techniques are suggested for protecting the privacy of respondents and reducing the response bias while eliciting information on sensitive attributes. In many sensitive question surveys, the same population is often sampled repeatedly on each occasion. In this paper, we apply successive sampling scheme to improve the estimation of the sensitive proportion on current occasion.

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

Science.gov (United States)

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

A two-phase sampling design for increasing detections of rare species in occupancy surveys

Science.gov (United States)

Pacifici, Krishna; Dorazio, Robert M.; Dorazio, Michael J.

2012-01-01

1. Occupancy estimation is a commonly used tool in ecological studies owing to the ease at which data can be collected and the large spatial extent that can be covered. One major obstacle to using an occupancy-based approach is the complications associated with designing and implementing an efficient survey. These logistical challenges become magnified when working with rare species when effort can be wasted in areas with none or very few individuals. 2. Here, we develop a two-phase sampling approach that mitigates these problems by using a design that places more effort in areas with higher predicted probability of occurrence. We compare our new sampling design to traditional single-season occupancy estimation under a range of conditions and population characteristics. We develop an intuitive measure of predictive error to compare the two approaches and use simulations to assess the relative accuracy of each approach. 3. Our two-phase approach exhibited lower predictive error rates compared to the traditional single-season approach in highly spatially correlated environments. The difference was greatest when detection probability was high (0·75) regardless of the habitat or sample size. When the true occupancy rate was below 0·4 (0·05-0·4), we found that allocating 25% of the sample to the first phase resulted in the lowest error rates. 4. In the majority of scenarios, the two-phase approach showed lower error rates compared to the traditional single-season approach suggesting our new approach is fairly robust to a broad range of conditions and design factors and merits use under a wide variety of settings. 5. Synthesis and applications. Conservation and management of rare species are a challenging task facing natural resource managers. It is critical for studies involving rare species to efficiently allocate effort and resources as they are usually of a finite nature. We believe our approach provides a framework for optimal allocation of effort while

Sampling design for the Study of Cardiovascular Risks in Adolescents (ERICA

Directory of Open Access Journals (Sweden)

Mauricio Teixeira Leite de Vasconcellos

2015-05-01

Full Text Available The Study of Cardiovascular Risk in Adolescents (ERICA aims to estimate the prevalence of cardiovascular risk factors and metabolic syndrome in adolescents (12-17 years enrolled in public and private schools of the 273 municipalities with over 100,000 inhabitants in Brazil. The study population was stratified into 32 geographical strata (27 capitals and five sets with other municipalities in each macro-region of the country and a sample of 1,251 schools was selected with probability proportional to size. In each school three combinations of shift (morning and afternoon and grade were selected, and within each of these combinations, one class was selected. All eligible students in the selected classes were included in the study. The design sampling weights were calculated by the product of the reciprocals of the inclusion probabilities in each sampling stage, and were later calibrated considering the projections of the numbers of adolescents enrolled in schools located in the geographical strata by sex and age.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Science.gov (United States)

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Directory of Open Access Journals (Sweden)

David C Pavlacky

Full Text Available Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1 coordination across organizations and regions, 2 meaningful management and conservation objectives, and 3 rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17. We provide two examples for the Brewer's sparrow (Spizella breweri in BCR 17 demonstrating the ability of the design to 1 determine hierarchical population responses to landscape change and 2 estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous

A 172 $\\mu$W Compressively Sampled Photoplethysmographic (PPG) Readout ASIC With Heart Rate Estimation Directly From Compressively Sampled Data.

Science.gov (United States)

Pamula, Venkata Rajesh; Valero-Sarmiento, Jose Manuel; Yan, Long; Bozkurt, Alper; Hoof, Chris Van; Helleputte, Nick Van; Yazicioglu, Refet Firat; Verhelst, Marian

2017-06-01

A compressive sampling (CS) photoplethysmographic (PPG) readout with embedded feature extraction to estimate heart rate (HR) directly from compressively sampled data is presented. It integrates a low-power analog front end together with a digital back end to perform feature extraction to estimate the average HR over a 4 s interval directly from compressively sampled PPG data. The application-specified integrated circuit (ASIC) supports uniform sampling mode (1x compression) as well as CS modes with compression ratios of 8x, 10x, and 30x. CS is performed through nonuniformly subsampling the PPG signal, while feature extraction is performed using least square spectral fitting through Lomb-Scargle periodogram. The ASIC consumes 172  μ W of power from a 1.2 V supply while reducing the relative LED driver power consumption by up to 30 times without significant loss of relevant information for accurate HR estimation.

Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

Directory of Open Access Journals (Sweden)

Bruno Giacomini Sari

2017-09-01

Full Text Available ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.

Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

Science.gov (United States)

Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

2008-12-01

Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral

Bias correction of risk estimates in vaccine safety studies with rare adverse events using a self-controlled case series design.

Science.gov (United States)

Zeng, Chan; Newcomer, Sophia R; Glanz, Jason M; Shoup, Jo Ann; Daley, Matthew F; Hambidge, Simon J; Xu, Stanley

2013-12-15

The self-controlled case series (SCCS) method is often used to examine the temporal association between vaccination and adverse events using only data from patients who experienced such events. Conditional Poisson regression models are used to estimate incidence rate ratios, and these models perform well with large or medium-sized case samples. However, in some vaccine safety studies, the adverse events studied are rare and the maximum likelihood estimates may be biased. Several bias correction methods have been examined in case-control studies using conditional logistic regression, but none of these methods have been evaluated in studies using the SCCS design. In this study, we used simulations to evaluate 2 bias correction approaches-the Firth penalized maximum likelihood method and Cordeiro and McCullagh's bias reduction after maximum likelihood estimation-with small sample sizes in studies using the SCCS design. The simulations showed that the bias under the SCCS design with a small number of cases can be large and is also sensitive to a short risk period. The Firth correction method provides finite and less biased estimates than the maximum likelihood method and Cordeiro and McCullagh's method. However, limitations still exist when the risk period in the SCCS design is short relative to the entire observation period.

Estimating temporary emigration and breeding proportions using capture-recapture data with Pollock's robust design

Science.gov (United States)

Kendall, W.L.; Nichols, J.D.; Hines, J.E.

1997-01-01

Statistical inference for capture-recapture studies of open animal populations typically relies on the assumption that all emigration from the studied population is permanent. However, there are many instances in which this assumption is unlikely to be met. We define two general models for the process of temporary emigration, completely random and Markovian. We then consider effects of these two types of temporary emigration on Jolly-Seber (Seber 1982) estimators and on estimators arising from the full-likelihood approach of Kendall et al. (1995) to robust design data. Capture-recapture data arising from Pollock's (1982) robust design provide the basis for obtaining unbiased estimates of demographic parameters in the presence of temporary emigration and for estimating the probability of temporary emigration. We present a likelihood-based approach to dealing with temporary emigration that permits estimation under different models of temporary emigration and yields tests for completely random and Markovian emigration. In addition, we use the relationship between capture probability estimates based on closed and open models under completely random temporary emigration to derive three ad hoc estimators for the probability of temporary emigration, two of which should be especially useful in situations where capture probabilities are heterogeneous among individual animals. Ad hoc and full-likelihood estimators are illustrated for small mammal capture-recapture data sets. We believe that these models and estimators will be useful for testing hypotheses about the process of temporary emigration, for estimating demographic parameters in the presence of temporary emigration, and for estimating probabilities of temporary emigration. These latter estimates are frequently of ecological interest as indicators of animal movement and, in some sampling situations, as direct estimates of breeding probabilities and proportions.

Sampling effects on the identification of roadkill hotspots: Implications for survey design.

Science.gov (United States)

Santos, Sara M; Marques, J Tiago; Lourenço, André; Medinas, Denis; Barbosa, A Márcia; Beja, Pedro; Mira, António

2015-10-01

Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. "True" hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. "Estimated" hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1-30 days). Overall, 24.3% of segments were "true" hotspots, concentrating 40.4% of roadkills. For different groups, "true" hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from 60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between "true" and "estimated" hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing "true" hotspots). There were also false positives (i.e., wrong "estimated" hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores). Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accurate Frequency Estimation Based On Three-Parameter Sine-Fitting With Three FFT Samples

Directory of Open Access Journals (Sweden)

Liu Xin

2015-09-01

Full Text Available This paper presents a simple DFT-based golden section searching algorithm (DGSSA for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT and Discrete Fourier Transform (DFT are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accuracy under conditions of a low signal-to-noise ratio (SNR and a low resolution. This method firstly uses three FFT samples to determine the frequency searching scope, then – besides the frequency – the estimated values of amplitude, phase and dc component are obtained by minimizing the least square (LS fitting error of three-parameter sine fitting. By setting reasonable stop conditions or the number of iterations, the accurate frequency estimation can be realized. The accuracy of this method, when applied to observed single-tone sinusoid samples corrupted by white Gaussian noise, is investigated by different methods with respect to the unbiased Cramer-Rao Low Bound (CRLB. The simulation results show that the root mean square error (RMSE of the frequency estimation curve is consistent with the tendency of CRLB as SNR increases, even in the case of a small number of samples. The average RMSE of the frequency estimation is less than 1.5 times the CRLB with SNR = 20 dB and N = 512.

Increasing fMRI sampling rate improves Granger causality estimates.

Directory of Open Access Journals (Sweden)

Fa-Hsuan Lin

Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

Microcontroller-based system for estimate of calcium in serum samples.

Science.gov (United States)

Neelamegam, Periyaswmy; Jamaludeen, Abdul Sheriff; Ragendran, Annamalai; Murugrananthan, Krishanamoorthy

2010-01-01

In this study, a microcontroller-based control unit was designed and constructed for the estimation of serum calcium in blood samples. The proposed optoelectronic instrument used a red light emitting diode (LED) as a light source and photodiode as a sensor. The performance of the system was compared with that of a commercial instrument in measuring calcium ion. The quantitative analysis of calcium in a catalyst using arsenazo III as colorimetric reagent was used to test the device. The calibration curve for calcium binding with arsenazo III was drawn to check the range of linearity, which was between 0.1 to 4.5 mM L⁻¹. The limit of detection (LOD) is 0.05 mM L⁻¹. Absorbance changes over the pH range of 2-12 were determined to optimize the assay, with maximum absorption at pH 9.0. Interferences in absorbance from monovalent (K+ and Na+) and divalent (Mg²+) cations were also studied. The results show that the system works successfully.

Zinc estimates in ore and slag samples and analysis of ash in coal samples

International Nuclear Information System (INIS)

Umamaheswara Rao, K.; Narayana, D.G.S.; Subrahmanyam, Y.

1984-01-01

Zinc estimates in ore and slag samples were made using the radioisotope X-ray fluorescence method. A 10 mCi 238 Pu was employed as the primary source of radiation and a thin crystal NaI(Ti) spectrometer was used to accomplish the detection of the 8.64 keV Zinc K-characteristic X-ray line. The results are reported. Ash content of coal concerning about 100 samples from Ravindra Khani VI and VII mines in Andhra Pradesh were measured using X-ray backscattering method with compensation for varying concentrations of iron in different coal samples through iron-X-ray fluorescent intensity measurements. The ash percent is found to range from 10 to 40. (author)

A two-stage Bayesian design with sample size reestimation and subgroup analysis for phase II binary response trials.

Science.gov (United States)

Zhong, Wei; Koopmeiners, Joseph S; Carlin, Bradley P

2013-11-01

Frequentist sample size determination for binary outcome data in a two-arm clinical trial requires initial guesses of the event probabilities for the two treatments. Misspecification of these event rates may lead to a poor estimate of the necessary sample size. In contrast, the Bayesian approach that considers the treatment effect to be random variable having some distribution may offer a better, more flexible approach. The Bayesian sample size proposed by (Whitehead et al., 2008) for exploratory studies on efficacy justifies the acceptable minimum sample size by a "conclusiveness" condition. In this work, we introduce a new two-stage Bayesian design with sample size reestimation at the interim stage. Our design inherits the properties of good interpretation and easy implementation from Whitehead et al. (2008), generalizes their method to a two-sample setting, and uses a fully Bayesian predictive approach to reduce an overly large initial sample size when necessary. Moreover, our design can be extended to allow patient level covariates via logistic regression, now adjusting sample size within each subgroup based on interim analyses. We illustrate the benefits of our approach with a design in non-Hodgkin lymphoma with a simple binary covariate (patient gender), offering an initial step toward within-trial personalized medicine. Copyright © 2013 Elsevier Inc. All rights reserved.

Design compliance matrix waste sample container filling system for nested, fixed-depth sampling system

International Nuclear Information System (INIS)

BOGER, R.M.

1999-01-01

This design compliance matrix document provides specific design related functional characteristics, constraints, and requirements for the container filling system that is part of the nested, fixed-depth sampling system. This document addresses performance, external interfaces, ALARA, Authorization Basis, environmental and design code requirements for the container filling system. The container filling system will interface with the waste stream from the fluidic pumping channels of the nested, fixed-depth sampling system and will fill containers with waste that meet the Resource Conservation and Recovery Act (RCRA) criteria for waste that contains volatile and semi-volatile organic materials. The specifications for the nested, fixed-depth sampling system are described in a Level 2 Specification document (HNF-3483, Rev. 1). The basis for this design compliance matrix document is the Tank Waste Remediation System (TWRS) desk instructions for design Compliance matrix documents (PI-CP-008-00, Rev. 0)

Design flood estimation in ungauged basins: probabilistic extension of the design-storm concept

Science.gov (United States)

Berk, Mario; Špačková, Olga; Straub, Daniel

2016-04-01

Design flood estimation in ungauged basins is an important hydrological task, which is in engineering practice typically solved with the design storm concept. However, neglecting the uncertainty in the hydrological response of the catchment through the assumption of average-recurrence-interval (ARI) neutrality between rainfall and runoff can lead to flawed design flood estimates. Additionally, selecting a single critical rainfall duration neglects the contribution of other rainfall durations on the probability of extreme flood events. In this study, the design flood problem is approached with concepts from structural reliability that enable a consistent treatment of multiple uncertainties in estimating the design flood. The uncertainty of key model parameters are represented probabilistically and the First-Order Reliability Method (FORM) is used to compute the flood exceedance probability. As an important by-product, the FORM analysis provides the most likely parameter combination to lead to a flood with a certain exceedance probability; i.e. it enables one to find representative scenarios for e.g., a 100 year or a 1000 year flood. Possible different rainfall durations are incorporated by formulating the event of a given design flood as a series system. The method is directly applicable in practice, since for the description of the rainfall depth-duration characteristics, the same inputs as for the classical design storm methods are needed, which are commonly provided by meteorological services. The proposed methodology is applied to a case study of Trauchgauer Ach catchment in Bavaria, SCS Curve Number (CN) and Unit hydrograph models are used for modeling the hydrological process. The results indicate, in accordance with past experience, that the traditional design storm concept underestimates design floods.

Infusion and sampling site effects on two-pool model estimates of leucine metabolism

International Nuclear Information System (INIS)

Helland, S.J.; Grisdale-Helland, B.; Nissen, S.

1988-01-01

To assess the effect of site of isotope infusion on estimates of leucine metabolism infusions of alpha-[4,5-3H]ketoisocaproate (KIC) and [U- 14 C]leucine were made into the left or right ventricles of sheep and pigs. Blood was sampled from the opposite ventricle. In both species, left ventricular infusions resulted in significantly lower specific radioactivities (SA) of [ 14 C]leucine and [ 3 H]KIC. [ 14 C]KIC SA was found to be insensitive to infusion and sampling sites. [ 14 C]KIC was in addition found to be equal to the SA of [ 14 C]leucine only during the left heart infusions. Therefore, [ 14 C]KIC SA was used as the only estimate for [ 14 C]SA in the equations for the two-pool model. This model eliminated the influence of site of infusion and blood sampling on the estimates for leucine entry and reduced the impact on the estimates for proteolysis and oxidation. This two-pool model could not compensate for the underestimation of transamination reactions occurring during the traditional venous isotope infusion and arterial blood sampling

Reduced design load basis for ultimate blade loads estimation in multidisciplinary design optimization frameworks

DEFF Research Database (Denmark)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.

2016-01-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost...... function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed...... for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar...

Sample design for the residential energy consumption survey

Energy Technology Data Exchange (ETDEWEB)

1994-08-01

The purpose of this report is to provide detailed information about the multistage area-probability sample design used for the Residential Energy Consumption Survey (RECS). It is intended as a technical report, for use by statisticians, to better understand the theory and procedures followed in the creation of the RECS sample frame. For a more cursory overview of the RECS sample design, refer to the appendix entitled ``How the Survey was Conducted,`` which is included in the statistical reports produced for each RECS survey year.

Sample size methodology

CERN Document Server

Desu, M M

2012-01-01

One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropria

System design description for sampling fuel in K basins

International Nuclear Information System (INIS)

Baker, R.B.

1996-01-01

This System Design Description provides: (1) statements of the Spent Nuclear Fuel Projects (SNFP) needs requiring sampling of fuel in the K East and K West Basins, (2) the sampling equipment functions and requirements, (3) a general work plan and the design logic being followed to develop the equipment, and (4) a summary description of the design for the sampling equipment. The report summarizes the integrated application of both the subject equipment and the canister sludge sampler in near-term characterization campaigns at K Basins

Sampling design for use by the soil decontamination project

International Nuclear Information System (INIS)

Rutherford, D.W.; Stevens, J.R.

1981-01-01

This report proposes a general approach to the problem and discusses sampling of soil to map the contaminated area and to provide samples for characterizaton of soil components and contamination. Basic concepts in sample design are reviewed with reference to environmental transuranic studies. Common designs are reviewed and evaluated for use with specific objectives that might be required by the soil decontamination project. Examples of a hierarchial design pilot study and a combined hierarchial and grid study are proposed for the Rocky Flats 903 pad area

[Saarland Growth Study: sampling design].

Science.gov (United States)

Danker-Hopfe, H; Zabransky, S

2000-01-01

The use of reference data to evaluate the physical development of children and adolescents is part of the daily routine in the paediatric ambulance. The construction of such reference data is based on the collection of extensive reference data. There are different kinds of reference data: cross sectional references, which are based on data collected from a big representative cross-sectional sample of the population, longitudinal references, which are based on follow-up surveys of usually smaller samples of individuals from birth to maturity, and mixed longitudinal references, which are a combination of longitudinal and cross-sectional reference data. The advantages and disadvantages of the different methods of data collection and the resulting reference data are discussed. The Saarland Growth Study was conducted for several reasons: growth processes are subject to secular changes, there are no specific reference data for children and adolescents from this part of the country and the growth charts in use in the paediatric praxis are possibly not appropriate any more. Therefore, the Saarland Growth Study served two purposes a) to create actual regional reference data and b) to create a database for future studies on secular trends in growth processes of children and adolescents from Saarland. The present contribution focusses on general remarks on the sampling design of (cross-sectional) growth surveys and its inferences for the design of the present study.

The impact of fecal sample processing on prevalence estimates for antibiotic-resistant Escherichia coli.

Science.gov (United States)

Omulo, Sylvia; Lofgren, Eric T; Mugoh, Maina; Alando, Moshe; Obiya, Joshua; Kipyegon, Korir; Kikwai, Gilbert; Gumbi, Wilson; Kariuki, Samuel; Call, Douglas R

2017-05-01

Investigators often rely on studies of Escherichia coli to characterize the burden of antibiotic resistance in a clinical or community setting. To determine if prevalence estimates for antibiotic resistance are sensitive to sample handling and interpretive criteria, we collected presumptive E. coli isolates (24 or 95 per stool sample) from a community in an urban informal settlement in Kenya. Isolates were tested for susceptibility to nine antibiotics using agar breakpoint assays and results were analyzed using generalized linear mixed models. We observed a 0.1). Prevalence estimates did not differ for five distinct E. coli colony morphologies on MacConkey agar plates (P>0.2). Successive re-plating of samples for up to five consecutive days had little to no impact on prevalence estimates. Finally, culturing E. coli under different conditions (with 5% CO 2 or micro-aerobic) did not affect estimates of prevalence. For the conditions tested in these experiments, minor modifications in sample processing protocols are unlikely to bias estimates of the prevalence of antibiotic-resistance for fecal E. coli. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimates of laboratory accuracy and precision on Hanford waste tank samples

International Nuclear Information System (INIS)

Dodd, D.A.

1995-01-01

A review was performed on three sets of analyses generated in Battelle, Pacific Northwest Laboratories and three sets generated by Westinghouse Hanford Company, 222-S Analytical Laboratory. Laboratory accuracy and precision was estimated by analyte and is reported in tables. The sources used to generate this estimate is of limited size but does include the physical forms, liquid and solid, which are representative of samples from tanks to be characterized. This estimate was published as an aid to programs developing data quality objectives in which specified limits are established. Data resulting from routine analyses of waste matrices can be expected to be bounded by the precision and accuracy estimates of the tables. These tables do not preclude or discourage direct negotiations between program and laboratory personnel while establishing bounding conditions. Programmatic requirements different than those listed may be reliably met on specific measurements and matrices. It should be recognized, however, that these are specific to waste tank matrices and may not be indicative of performance on samples from other sources

Design and development of multiple sample counting setup

International Nuclear Information System (INIS)

Rath, D.P.; Murali, S.; Babu, D.A.R.

2010-01-01

Full text: The analysis of active samples on regular basis for ambient air activity and floor contamination from radio chemical lab accounts for major chunk of the operational activity in Health Physicist's responsibility. The requirement for daily air sample analysis on immediate counting and delayed counting from various labs in addition to samples of smear swipe check of lab led to the urge for development of system that could cater multiple sample analysis in a time programmed manner on a single sample loading. A multiple alpha/beta counting system for counting was designed and fabricated. It has arrangements for loading 10 samples in slots in order, get counted in a time programmed manner with results displayed and records maintained in PC. The paper describes the design and development of multiple sample counting setup presently in use at the facility has resulted in reduction of man-hour consumption in counting and recording of the results

Estimation of tritium activity in bioassay samples having chemiluminescence

International Nuclear Information System (INIS)

Dwivedi, R.K.; Manu, Kumar; Kumar, Vinay; Soni, Ashish; Kaushik, A.K.; Tiwari, S.K.; Gupta, Ashok

2008-01-01

Tritium is recognized as major internal dose contributor in PHWR type of reactors. Estimation of internal dose due to tritium is carried out by analyzing urine samples in liquid scintillation analyzer (LSA). Presence of residual biochemical species in urine samples of some individuals under medical administration shows significant amount of chemiluminescence. If appropriate care is not taken the results obtained by liquid scintillation counter may be mistaken as genuine uptake of tritium. The distillation method described in this paper is used at RAPS-3 and 4 to assess correct tritium uptake. (author)

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.

Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation

International Nuclear Information System (INIS)

Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.

2016-01-01

In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also

Sensitivity of Process Design due to Uncertainties in Property Estimates

DEFF Research Database (Denmark)

Hukkerikar, Amol; Jones, Mark Nicholas; Sarup, Bent

2012-01-01

The objective of this paper is to present a systematic methodology for performing analysis of sensitivity of process design due to uncertainties in property estimates. The methodology provides the following results: a) list of properties with critical importance on design; b) acceptable levels of...... in chemical processes. Among others vapour pressure accuracy for azeotropic mixtures is critical and needs to be measured or estimated with a ±0.25% accuracy to satisfy acceptable safety levels in design....

Designing an enhanced groundwater sample collection system

International Nuclear Information System (INIS)

Schalla, R.

1994-10-01

As part of an ongoing technical support mission to achieve excellence and efficiency in environmental restoration activities at the Laboratory for Energy and Health-Related Research (LEHR), Pacific Northwest Laboratory (PNL) provided guidance on the design and construction of monitoring wells and identified the most suitable type of groundwater sampling pump and accessories for monitoring wells. The goal was to utilize a monitoring well design that would allow for hydrologic testing and reduce turbidity to minimize the impact of sampling. The sampling results of the newly designed monitoring wells were clearly superior to those of the previously installed monitoring wells. The new wells exhibited reduced turbidity, in addition to improved access for instrumentation and hydrologic testing. The variable frequency submersible pump was selected as the best choice for obtaining groundwater samples. The literature references are listed at the end of this report. Despite some initial difficulties, the actual performance of the variable frequency, submersible pump and its accessories was effective in reducing sampling time and labor costs, and its ease of use was preferred over the previously used bladder pumps. The surface seals system, called the Dedicator, proved to be useful accessory to prevent surface contamination while providing easy access for water-level measurements and for connecting the pump. Cost savings resulted from the use of the pre-production pumps (beta units) donated by the manufacturer for the demonstration. However, larger savings resulted from shortened field time due to the ease in using the submersible pumps and the surface seal access system. Proper deployment of the monitoring wells also resulted in cost savings and ensured representative samples

Identification and estimation of nonlinear models using two samples with nonclassical measurement errors

KAUST Repository

Carroll, Raymond J.

2010-05-01

This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, without either instrumental variables or independence between the two samples. When the two samples are independent and the nonlinear regression model is parameterized, we propose sieve Quasi Maximum Likelihood Estimation (Q-MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification, with easily estimated standard errors. A Monte Carlo simulation and a data application are presented to show the power of the approach.

Extending cluster lot quality assurance sampling designs for surveillance programs.

Science.gov (United States)

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

A generic tool for cost estimating in aircraft design

NARCIS (Netherlands)

Castagne, S.; Curran, R.; Rothwell, A.; Price, M.; Benard, E.; Raghunathan, S.

2008-01-01

A methodology to estimate the cost implications of design decisions by integrating cost as a design parameter at an early design stage is presented. The model is developed on a hierarchical basis, the manufacturing cost of aircraft fuselage panels being analysed in this paper. The manufacturing cost

Thermal probe design for Europa sample acquisition

Science.gov (United States)

Horne, Mera F.

2018-01-01

The planned lander missions to the surface of Europa will access samples from the subsurface of the ice in a search for signs of life. A small thermal drill (probe) is proposed to meet the sample requirement of the Science Definition Team's (SDT) report for the Europa mission. The probe is 2 cm in diameter and 16 cm in length and is designed to access the subsurface to 10 cm deep and to collect five ice samples of 7 cm3 each, approximately. The energy required to penetrate the top 10 cm of ice in a vacuum is 26 Wh, approximately, and to melt 7 cm3 of ice is 1.2 Wh, approximately. The requirement stated in the SDT report of collecting samples from five different sites can be accommodated with repeated use of the same thermal drill. For smaller sample sizes, a smaller probe of 1.0 cm in diameter with the same length of 16 cm could be utilized that would require approximately 6.4 Wh to penetrate the top 10 cm of ice, and 0.02 Wh to collect 0.1 g of sample. The thermal drill has the advantage of simplicity of design and operations and the ability to penetrate ice over a range of densities and hardness while maintaining sample integrity.

Analysis of Clinical Cohort Data Using Nested Case-control and Case-cohort Sampling Designs. A Powerful and Economical Tool.

Science.gov (United States)

Ohneberg, K; Wolkewitz, M; Beyersmann, J; Palomar-Martinez, M; Olaechea-Astigarraga, P; Alvarez-Lerma, F; Schumacher, M

2015-01-01

Sampling from a large cohort in order to derive a subsample that would be sufficient for statistical analysis is a frequently used method for handling large data sets in epidemiological studies with limited resources for exposure measurement. For clinical studies however, when interest is in the influence of a potential risk factor, cohort studies are often the first choice with all individuals entering the analysis. Our aim is to close the gap between epidemiological and clinical studies with respect to design and power considerations. Schoenfeld's formula for the number of events required for a Cox' proportional hazards model is fundamental. Our objective is to compare the power of analyzing the full cohort and the power of a nested case-control and a case-cohort design. We compare formulas for power for sampling designs and cohort studies. In our data example we simultaneously apply a nested case-control design with a varying number of controls matched to each case, a case cohort design with varying subcohort size, a random subsample and a full cohort analysis. For each design we calculate the standard error for estimated regression coefficients and the mean number of distinct persons, for whom covariate information is required. The formula for the power of a nested case-control design and the power of a case-cohort design is directly connected to the power of a cohort study using the well known Schoenfeld formula. The loss in precision of parameter estimates is relatively small compared to the saving in resources. Nested case-control and case-cohort studies, but not random subsamples yield an attractive alternative for analyzing clinical studies in the situation of a low event rate. Power calculations can be conducted straightforwardly to quantify the loss of power compared to the savings in the num-ber of patients using a sampling design instead of analyzing the full cohort.

Reliability estimation system: its application to the nuclear geophysical sampling of ore deposits

International Nuclear Information System (INIS)

Khaykovich, I.M.; Savosin, S.I.

1992-01-01

The reliability estimation system accepted in the Soviet Union for sampling data in nuclear geophysics is based on unique requirements in metrology and methodology. It involves estimating characteristic errors in calibration, as well as errors in measurement and interpretation. This paper describes the methods of estimating the levels of systematic and random errors at each stage of the problem. The data of nuclear geophysics sampling are considered to be reliable if there are no statistically significant, systematic differences between ore intervals determined by this method and by geological control, or by other methods of sampling; the reliability of the latter having been verified. The difference between the random errors is statistically insignificant. The system allows one to obtain information on the parameters of ore intervals with a guaranteed random error and without systematic errors. (Author)

Adaptive clinical trial designs with pre-specified rules for modifying the sample size: understanding efficient types of adaptation.

Science.gov (United States)

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2013-04-15

Adaptive clinical trial design has been proposed as a promising new approach that may improve the drug discovery process. Proponents of adaptive sample size re-estimation promote its ability to avoid 'up-front' commitment of resources, better address the complicated decisions faced by data monitoring committees, and minimize accrual to studies having delayed ascertainment of outcomes. We investigate aspects of adaptation rules, such as timing of the adaptation analysis and magnitude of sample size adjustment, that lead to greater or lesser statistical efficiency. Owing in part to the recent Food and Drug Administration guidance that promotes the use of pre-specified sampling plans, we evaluate alternative approaches in the context of well-defined, pre-specified adaptation. We quantify the relative costs and benefits of fixed sample, group sequential, and pre-specified adaptive designs with respect to standard operating characteristics such as type I error, maximal sample size, power, and expected sample size under a range of alternatives. Our results build on others' prior research by demonstrating in realistic settings that simple and easily implemented pre-specified adaptive designs provide only very small efficiency gains over group sequential designs with the same number of analyses. In addition, we describe optimal rules for modifying the sample size, providing efficient adaptation boundaries on a variety of scales for the interim test statistic for adaptation analyses occurring at several different stages of the trial. We thus provide insight into what are good and bad choices of adaptive sampling plans when the added flexibility of adaptive designs is desired. Copyright © 2012 John Wiley & Sons, Ltd.

Is a 'convenience' sample useful for estimating immunization coverage in a small population?

Science.gov (United States)

Weir, Jean E; Jones, Carrie

2008-01-01

Rapid survey methodologies are widely used for assessing immunization coverage in developing countries, approximating true stratified random sampling. Non-random ('convenience') sampling is not considered appropriate for estimating immunization coverage rates but has the advantages of low cost and expediency. We assessed the validity of a convenience sample of children presenting to a travelling clinic by comparing the coverage rate in the convenience sample to the true coverage established by surveying each child in three villages in rural Papua New Guinea. The rate of DTF immunization coverage as estimated by the convenience sample was within 10% of the true coverage when the proportion of children in the sample was two-thirds or when only children over the age of one year were counted, but differed by 11% when the sample included only 53% of the children and when all eligible children were included. The convenience sample may be sufficiently accurate for reporting purposes and is useful for identifying areas of low coverage.

Evaluating the performance of species richness estimators: sensitivity to sample grain size

DEFF Research Database (Denmark)

Hortal, Joaquín; Borges, Paulo A. V.; Gaspar, Clara

2006-01-01

and several recent estimators [proposed by Rosenzweig et al. (Conservation Biology, 2003, 17, 864-874), and Ugland et al. (Journal of Animal Ecology, 2003, 72, 888-897)] performed poorly. 3.  Estimations developed using the smaller grain sizes (pair of traps, traps, records and individuals) presented similar....... Data obtained with standardized sampling of 78 transects in natural forest remnants of five islands were aggregated in seven different grains (i.e. ways of defining a single sample): islands, natural areas, transects, pairs of traps, traps, database records and individuals to assess the effect of using...

Bayesian Estimation of Fish Disease Prevalence from Pooled Samples Incorporating Sensitivity and Specificity

Science.gov (United States)

Williams, Christopher J.; Moffitt, Christine M.

2003-03-01

An important emerging issue in fisheries biology is the health of free-ranging populations of fish, particularly with respect to the prevalence of certain pathogens. For many years, pathologists focused on captive populations and interest was in the presence or absence of certain pathogens, so it was economically attractive to test pooled samples of fish. Recently, investigators have begun to study individual fish prevalence from pooled samples. Estimation of disease prevalence from pooled samples is straightforward when assay sensitivity and specificity are perfect, but this assumption is unrealistic. Here we illustrate the use of a Bayesian approach for estimating disease prevalence from pooled samples when sensitivity and specificity are not perfect. We also focus on diagnostic plots to monitor the convergence of the Gibbs-sampling-based Bayesian analysis. The methods are illustrated with a sample data set.

Network Model-Assisted Inference from Respondent-Driven Sampling Data.

Science.gov (United States)

Gile, Krista J; Handcock, Mark S

2015-06-01

Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population.

Porosity estimation by semi-supervised learning with sparsely available labeled samples

Science.gov (United States)

Lima, Luiz Alberto; Görnitz, Nico; Varella, Luiz Eduardo; Vellasco, Marley; Müller, Klaus-Robert; Nakajima, Shinichi

2017-09-01

This paper addresses the porosity estimation problem from seismic impedance volumes and porosity samples located in a small group of exploratory wells. Regression methods, trained on the impedance as inputs and the porosity as output labels, generally suffer from extremely expensive (and hence sparsely available) porosity samples. To optimally make use of the valuable porosity data, a semi-supervised machine learning method was proposed, Transductive Conditional Random Field Regression (TCRFR), showing good performance (Görnitz et al., 2017). TCRFR, however, still requires more labeled data than those usually available, which creates a gap when applying the method to the porosity estimation problem in realistic situations. In this paper, we aim to fill this gap by introducing two graph-based preprocessing techniques, which adapt the original TCRFR for extremely weakly supervised scenarios. Our new method outperforms the previous automatic estimation methods on synthetic data and provides a comparable result to the manual labored, time-consuming geostatistics approach on real data, proving its potential as a practical industrial tool.

Seasonal and temporal variation in release of antibiotics in hospital wastewater: estimation using continuous and grab sampling.

Science.gov (United States)

Diwan, Vishal; Stålsby Lundborg, Cecilia; Tamhankar, Ashok J

2013-01-01

The presence of antibiotics in the environment and their subsequent impact on resistance development has raised concerns globally. Hospitals are a major source of antibiotics released into the environment. To reduce these residues, research to improve knowledge of the dynamics of antibiotic release from hospitals is essential. Therefore, we undertook a study to estimate seasonal and temporal variation in antibiotic release from two hospitals in India over a period of two years. For this, 6 sampling sessions of 24 hours each were conducted in the three prominent seasons of India, at all wastewater outlets of the two hospitals, using continuous and grab sampling methods. An in-house wastewater sampler was designed for continuous sampling. Eight antibiotics from four major antibiotic groups were selected for the study. To understand the temporal pattern of antibiotic release, each of the 24-hour sessions were divided in three sub-sampling sessions of 8 hours each. Solid phase extraction followed by liquid chromatography/tandem mass spectrometry (LC-MS/MS) was used to determine the antibiotic residues. Six of the eight antibiotics studied were detected in the wastewater samples. Both continuous and grab sampling methods indicated that the highest quantities of fluoroquinolones were released in winter followed by the rainy season and the summer. No temporal pattern in antibiotic release was detected. In general, in a common timeframe, continuous sampling showed less concentration of antibiotics in wastewater as compared to grab sampling. It is suggested that continuous sampling should be the method of choice as grab sampling gives erroneous results, it being indicative of the quantities of antibiotics present in wastewater only at the time of sampling. Based on our studies, calculations indicate that from hospitals in India, an estimated 89, 1 and 25 ng/L/day of fluroquinolones, metronidazole and sulfamethoxazole respectively, might be getting released into the

Comparison of chlorzoxazone one-sample methods to estimate CYP2E1 activity in humans

DEFF Research Database (Denmark)

Kramer, Iza; Dalhoff, Kim; Clemmesen, Jens O

2003-01-01

OBJECTIVE: Comparison of a one-sample with a multi-sample method (the metabolic fractional clearance) to estimate CYP2E1 activity in humans. METHODS: Healthy, male Caucasians ( n=19) were included. The multi-sample fractional clearance (Cl(fe)) of chlorzoxazone was compared with one...... estimates, Cl(est) at 3 h or 6 h, and MR at 3 h, can serve as reliable markers of CYP2E1 activity. The one-sample clearance method is an accurate, renal function-independent measure of the intrinsic activity; it is simple to use and easily applicable to humans.......-time-point clearance estimation (Cl(est)) at 3, 4, 5 and 6 h. Furthermore, the metabolite/drug ratios (MRs) estimated from one-time-point samples at 1, 2, 3, 4, 5 and 6 h were compared with Cl(fe). RESULTS: The concordance between Cl(est) and Cl(fe) was highest at 6 h. The minimal mean prediction error (MPE) of Cl...

Estimation of Uncertainty in Aerosol Concentration Measured by Aerosol Sampling System

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Chan; Song, Yong Jae; Jung, Woo Young; Lee, Hyun Chul; Kim, Gyu Tae; Lee, Doo Yong [FNC Technology Co., Yongin (Korea, Republic of)

2016-10-15

FNC Technology Co., Ltd has been developed test facilities for the aerosol generation, mixing, sampling and measurement under high pressure and high temperature conditions. The aerosol generation system is connected to the aerosol mixing system which injects SiO{sub 2}/ethanol mixture. In the sampling system, glass fiber membrane filter has been used to measure average mass concentration. Based on the experimental results using main carrier gas of steam and air mixture, the uncertainty estimation of the sampled aerosol concentration was performed by applying Gaussian error propagation law. FNC Technology Co., Ltd. has been developed the experimental facilities for the aerosol measurement under high pressure and high temperature. The purpose of the tests is to develop commercial test module for aerosol generation, mixing and sampling system applicable to environmental industry and safety related system in nuclear power plant. For the uncertainty calculation of aerosol concentration, the value of the sampled aerosol concentration is not measured directly, but must be calculated from other quantities. The uncertainty of the sampled aerosol concentration is a function of flow rates of air and steam, sampled mass, sampling time, condensed steam mass and its absolute errors. These variables propagate to the combination of variables in the function. Using operating parameters and its single errors from the aerosol test cases performed at FNC, the uncertainty of aerosol concentration evaluated by Gaussian error propagation law is less than 1%. The results of uncertainty estimation in the aerosol sampling system will be utilized for the system performance data.

An estimate and evaluation of design error effects on nuclear power plant design adequacy

International Nuclear Information System (INIS)

Stevenson, J.D.

1984-01-01

An area of considerable concern in evaluating Design Control Quality Assurance procedures applied to design and analysis of nuclear power plant is the level of design error expected or encountered. There is very little published data 1 on the level of error typically found in nuclear power plant design calculations and even less on the impact such errors would be expected to have on overall design adequacy of the plant. This paper is concerned with design error associated with civil and mechanical structural design and analysis found in calculations which form part of the Design or Stress reports. These reports are meant to document the design basis and adequacy of the plant. The estimates contained in this paper are based on the personal experiences of the author. In Table 1 is a partial listing of the design docummentation review performed by the author on which the observations contained in this paper are based. In the preparation of any design calculations, it is a utopian dream to presume such calculations can be made error free. The intent of this paper is to define error levels which might be expected in a competent engineering organizations employing currently technically qualified engineers and accepted methods of Design Control. In addition, the effects of these errors on the probability of failure to meet applicable design code requirements also are estimated

Experimental design for estimating parameters of rate-limited mass transfer: Analysis of stream tracer studies

Science.gov (United States)

Wagner, Brian J.; Harvey, Judson W.

1997-01-01

Tracer experiments are valuable tools for analyzing the transport characteristics of streams and their interactions with shallow groundwater. The focus of this work is the design of tracer studies in high-gradient stream systems subject to advection, dispersion, groundwater inflow, and exchange between the active channel and zones in surface or subsurface water where flow is stagnant or slow moving. We present a methodology for (1) evaluating and comparing alternative stream tracer experiment designs and (2) identifying those combinations of stream transport properties that pose limitations to parameter estimation and therefore a challenge to tracer test design. The methodology uses the concept of global parameter uncertainty analysis, which couples solute transport simulation with parameter uncertainty analysis in a Monte Carlo framework. Two general conclusions resulted from this work. First, the solute injection and sampling strategy has an important effect on the reliability of transport parameter estimates. We found that constant injection with sampling through concentration rise, plateau, and fall provided considerably more reliable parameter estimates than a pulse injection across the spectrum of transport scenarios likely encountered in high-gradient streams. Second, for a given tracer test design, the uncertainties in mass transfer and storage-zone parameter estimates are strongly dependent on the experimental Damkohler number, DaI, which is a dimensionless combination of the rates of exchange between the stream and storage zones, the stream-water velocity, and the stream reach length of the experiment. Parameter uncertainties are lowest at DaI values on the order of 1.0. When DaI values are much less than 1.0 (owing to high velocity, long exchange timescale, and/or short reach length), parameter uncertainties are high because only a small amount of tracer interacts with storage zones in the reach. For the opposite conditions (DaI ≫ 1.0), solute

Design and construction of a prototype vaporization calorimeter for the assay of radioisotopic samples

International Nuclear Information System (INIS)

Tormey, T.V.

1979-10-01

A prototype vaporization calorimeter has been designed and constructed for use in the assay of low power output radioisotopic samples. The prototype calorimeter design was based on that of a previous experimental instrument used by H.P. Stephens, to establish the feasibility of the vaporization calorimetry technique for this type of power measurement. The calorimeter is composed of a mechanical calorimeter assembly together with a data acquisition and control system. Detailed drawings of the calorimeter assembly are included and additional drawings are referenced. The data acquisition system is based on an HP 9825A programmable calculator. A description of the hardware is provided together with a listing of all system software programs. The operating procedure is outlined, including initial setup and operation of all related equipment. Preliminary system performance was evaluated by making a series of four measurements on two nominal 1.5W samples and on a nominal 0.75W sample. Data for these measurements indicate that the absolute accuracy (one standard deviation) is approx. = 0.0035W in this power range, resulting in an estimated relative one standard deviation accuracy of 0.24% at 1.5W and 0.48% at 0.75W

inverse gaussian model for small area estimation via gibbs sampling

African Journals Online (AJOL)

ADMIN

For example, MacGibbon and Tomberlin. (1989) have considered estimating small area rates and binomial parameters using empirical Bayes methods. Stroud (1991) used hierarchical Bayes approach for univariate natural exponential families with quadratic variance functions in sample survey applications, while Chaubey ...

Limited sampling hampers "big data" estimation of species richness in a tropical biodiversity hotspot.

Science.gov (United States)

Engemann, Kristine; Enquist, Brian J; Sandel, Brody; Boyle, Brad; Jørgensen, Peter M; Morueta-Holme, Naia; Peet, Robert K; Violle, Cyrille; Svenning, Jens-Christian

2015-02-01

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with "big data" collections.

Beamforming using subspace estimation from a diagonally averaged sample covariance.

Science.gov (United States)

Quijano, Jorge E; Zurk, Lisa M

2017-08-01

The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.

The effects of parameter estimation on minimizing the in-control average sample size for the double sampling X bar chart

Directory of Open Access Journals (Sweden)

Michael B.C. Khoo

2013-11-01

Full Text Available The double sampling (DS X bar chart, one of the most widely-used charting methods, is superior for detecting small and moderate shifts in the process mean. In a right skewed run length distribution, the median run length (MRL provides a more credible representation of the central tendency than the average run length (ARL, as the mean is greater than the median. In this paper, therefore, MRL is used as the performance criterion instead of the traditional ARL. Generally, the performance of the DS X bar chart is investigated under the assumption of known process parameters. In practice, these parameters are usually estimated from an in-control reference Phase-I dataset. Since the performance of the DS X bar chart is significantly affected by estimation errors, we study the effects of parameter estimation on the MRL-based DS X bar chart when the in-control average sample size is minimised. This study reveals that more than 80 samples are required for the MRL-based DS X bar chart with estimated parameters to perform more favourably than the corresponding chart with known parameters.

ACS sampling system: design, implementation, and performance evaluation

Science.gov (United States)

Di Marcantonio, Paolo; Cirami, Roberto; Chiozzi, Gianluca

2004-09-01

By means of ACS (ALMA Common Software) framework we designed and implemented a sampling system which allows sampling of every Characteristic Component Property with a specific, user-defined, sustained frequency limited only by the hardware. Collected data are sent to various clients (one or more Java plotting widgets, a dedicated GUI or a COTS application) using the ACS/CORBA Notification Channel. The data transport is optimized: samples are cached locally and sent in packets with a lower and user-defined frequency to keep network load under control. Simultaneous sampling of the Properties of different Components is also possible. Together with the design and implementation issues we present the performance of the sampling system evaluated on two different platforms: on a VME based system using VxWorks RTOS (currently adopted by ALMA) and on a PC/104+ embedded platform using Red Hat 9 Linux operating system. The PC/104+ solution offers, as an alternative, a low cost PC compatible hardware environment with free and open operating system.

MR-based water content estimation in cartilage: design and validation of a method

DEFF Research Database (Denmark)

Shiguetomi Medina, Juan Manuel; Kristiansen, Maja Sophie; Ringgaard, Steffen

Purpose: Design and validation of an MR-based method that allows the calculation of the water content in cartilage tissue. Methods and Materials: Cartilage tissue T1 map based water content MR sequences were used on a 37 Celsius degree stable system. The T1 map intensity signal was analyzed on 6...... cartilage samples from living animals (pig) and on 8 gelatin samples which water content was already known. For the data analysis a T1 intensity signal map software analyzer used. Finally, the method was validated after measuring and comparing 3 more cartilage samples in a living animal (pig). The obtained...... map based water content sequences can provide information that, after being analyzed using a T1-map analysis software, can be interpreted as the water contained inside a cartilage tissue. The amount of water estimated using this method was similar to the one obtained at the dry-freeze procedure...

Network Model-Assisted Inference from Respondent-Driven Sampling Data

Science.gov (United States)

Gile, Krista J.; Handcock, Mark S.

2015-01-01

Summary Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population. PMID:26640328

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang

2013-02-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang; Hansen, Charles

2013-01-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

Sampling point selection for energy estimation in the quasicontinuum method

NARCIS (Netherlands)

Beex, L.A.A.; Peerlings, R.H.J.; Geers, M.G.D.

2010-01-01

The quasicontinuum (QC) method reduces computational costs of atomistic calculations by using interpolation between a small number of so-called repatoms to represent the displacements of the complete lattice and by selecting a small number of sampling atoms to estimate the total potential energy of

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

Science.gov (United States)

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Mobile Variable Depth Sampling System Design Study

International Nuclear Information System (INIS)

BOGER, R.M.

2000-01-01

A design study is presented for a mobile, variable depth sampling system (MVDSS) that will support the treatment and immobilization of Hanford LAW and HLW. The sampler can be deployed in a 4-inch tank riser and has a design that is based on requirements identified in the Level 2 Specification (latest revision). The waste feed sequence for the MVDSS is based on Phase 1, Case 3S6 waste feed sequence. Technical information is also presented that supports the design study

Mobile Variable Depth Sampling System Design Study

Energy Technology Data Exchange (ETDEWEB)

BOGER, R.M.

2000-08-25

A design study is presented for a mobile, variable depth sampling system (MVDSS) that will support the treatment and immobilization of Hanford LAW and HLW. The sampler can be deployed in a 4-inch tank riser and has a design that is based on requirements identified in the Level 2 Specification (latest revision). The waste feed sequence for the MVDSS is based on Phase 1, Case 3S6 waste feed sequence. Technical information is also presented that supports the design study.

Estimating fish swimming metrics and metabolic rates with accelerometers: the influence of sampling frequency.

Science.gov (United States)

Brownscombe, J W; Lennox, R J; Danylchuk, A J; Cooke, S J

2018-06-21

Accelerometry is growing in popularity for remotely measuring fish swimming metrics, but appropriate sampling frequencies for accurately measuring these metrics are not well studied. This research examined the influence of sampling frequency (1-25 Hz) with tri-axial accelerometer biologgers on estimates of overall dynamic body acceleration (ODBA), tail-beat frequency, swimming speed and metabolic rate of bonefish Albula vulpes in a swim-tunnel respirometer and free-swimming in a wetland mesocosm. In the swim tunnel, sampling frequencies of ≥ 5 Hz were sufficient to establish strong relationships between ODBA, swimming speed and metabolic rate. However, in free-swimming bonefish, estimates of metabolic rate were more variable below 10 Hz. Sampling frequencies should be at least twice the maximum tail-beat frequency to estimate this metric effectively, which is generally higher than those required to estimate ODBA, swimming speed and metabolic rate. While optimal sampling frequency probably varies among species due to tail-beat frequency and swimming style, this study provides a reference point with a medium body-sized sub-carangiform teleost fish, enabling researchers to measure these metrics effectively and maximize study duration. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Estimation of plant sampling uncertainty: an example based on chemical analysis of moss samples.

Science.gov (United States)

Dołęgowska, Sabina

2016-11-01

In order to estimate the level of uncertainty arising from sampling, 54 samples (primary and duplicate) of the moss species Pleurozium schreberi (Brid.) Mitt. were collected within three forested areas (Wierna Rzeka, Piaski, Posłowice Range) in the Holy Cross Mountains (south-central Poland). During the fieldwork, each primary sample composed of 8 to 10 increments (subsamples) was taken over an area of 10 m 2 whereas duplicate samples were collected in the same way at a distance of 1-2 m. Subsequently, all samples were triple rinsed with deionized water, dried, milled, and digested (8 mL HNO 3 (1:1) + 1 mL 30 % H 2 O 2 ) in a closed microwave system Multiwave 3000. The prepared solutions were analyzed twice for Cu, Fe, Mn, and Zn using FAAS and GFAAS techniques. All datasets were checked for normality and for normally distributed elements (Cu from Piaski, Zn from Posłowice, Fe, Zn from Wierna Rzeka). The sampling uncertainty was computed with (i) classical ANOVA, (ii) classical RANOVA, (iii) modified RANOVA, and (iv) range statistics. For the remaining elements, the sampling uncertainty was calculated with traditional and/or modified RANOVA (if the amount of outliers did not exceed 10 %) or classical ANOVA after Box-Cox transformation (if the amount of outliers exceeded 10 %). The highest concentrations of all elements were found in moss samples from Piaski, whereas the sampling uncertainty calculated with different statistical methods ranged from 4.1 to 22 %.

Design of Artificial Neural Network-Based pH Estimator

Directory of Open Access Journals (Sweden)

Shebel A. Alsabbah

2010-10-01

Full Text Available Taking into consideration the cost, size and drawbacks might be found with real hardware instrument for measuring pH values such that the complications of the wiring, installing, calibrating and troubleshooting the system, would make a person look for a cheaper, accurate, and alternative choice to perform the measuring operation, Where’s hereby, a feedforward artificial neural network-based pH estimator has to be proposed. The proposed estimator has been designed with multi- layer perceptrons. One input which is a measured base stream and two outputs represent pH values at strong base and strong/weak acids for a titration process. The created data base has been obtained with consideration of temperature variation. The final numerical results ensure the effectiveness and robustness of the design neural network-based pH estimator.

Semiparametric efficient and robust estimation of an unknown symmetric population under arbitrary sample selection bias

KAUST Repository

Ma, Yanyuan

2013-09-01

We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.

Critical length sampling: a method to estimate the volume of downed coarse woody debris

Science.gov (United States)

G& #246; ran St& #229; hl; Jeffrey H. Gove; Michael S. Williams; Mark J. Ducey

2010-01-01

In this paper, critical length sampling for estimating the volume of downed coarse woody debris is presented. Using this method, the volume of downed wood in a stand can be estimated by summing the critical lengths of down logs included in a sample obtained using a relascope or wedge prism; typically, the instrument should be tilted 90° from its usual...

Impact of sampling strategy on stream load estimates in till landscape of the Midwest

Science.gov (United States)

Vidon, P.; Hubbard, L.E.; Soyeux, E.

2009-01-01

Accurately estimating various solute loads in streams during storms is critical to accurately determine maximum daily loads for regulatory purposes. This study investigates the impact of sampling strategy on solute load estimates in streams in the US Midwest. Three different solute types (nitrate, magnesium, and dissolved organic carbon (DOC)) and three sampling strategies are assessed. Regardless of the method, the average error on nitrate loads is higher than for magnesium or DOC loads, and all three methods generally underestimate DOC loads and overestimate magnesium loads. Increasing sampling frequency only slightly improves the accuracy of solute load estimates but generally improves the precision of load calculations. This type of investigation is critical for water management and environmental assessment so error on solute load calculations can be taken into account by landscape managers, and sampling strategies optimized as a function of monitoring objectives. ?? 2008 Springer Science+Business Media B.V.

Comparison of prevalence estimation of Mycobacterium avium subsp. paratuberculosis infection by sampling slaughtered cattle with macroscopic lesions vs. systematic sampling.

Science.gov (United States)

Elze, J; Liebler-Tenorio, E; Ziller, M; Köhler, H

2013-07-01

The objective of this study was to identify the most reliable approach for prevalence estimation of Mycobacterium avium ssp. paratuberculosis (MAP) infection in clinically healthy slaughtered cattle. Sampling of macroscopically suspect tissue was compared to systematic sampling. Specimens of ileum, jejunum, mesenteric and caecal lymph nodes were examined for MAP infection using bacterial microscopy, culture, histopathology and immunohistochemistry. MAP was found most frequently in caecal lymph nodes, but sampling more tissues optimized the detection rate. Examination by culture was most efficient while combination with histopathology increased the detection rate slightly. MAP was detected in 49/50 animals with macroscopic lesions representing 1.35% of the slaughtered cattle examined. Of 150 systematically sampled macroscopically non-suspect cows, 28.7% were infected with MAP. This indicates that the majority of MAP-positive cattle are slaughtered without evidence of macroscopic lesions and before clinical signs occur. For reliable prevalence estimation of MAP infection in slaughtered cattle, systematic random sampling is essential.

Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators

International Nuclear Information System (INIS)

Flammia, Steven T; Gross, David; Liu, Yi-Kai; Eisert, Jens

2012-01-01

Intuitively, if a density operator has small rank, then it should be easier to estimate from experimental data, since in this case only a few eigenvectors need to be learned. We prove two complementary results that confirm this intuition. Firstly, we show that a low-rank density matrix can be estimated using fewer copies of the state, i.e. the sample complexity of tomography decreases with the rank. Secondly, we show that unknown low-rank states can be reconstructed from an incomplete set of measurements, using techniques from compressed sensing and matrix completion. These techniques use simple Pauli measurements, and their output can be certified without making any assumptions about the unknown state. In this paper, we present a new theoretical analysis of compressed tomography, based on the restricted isometry property for low-rank matrices. Using these tools, we obtain near-optimal error bounds for the realistic situation where the data contain noise due to finite statistics, and the density matrix is full-rank with decaying eigenvalues. We also obtain upper bounds on the sample complexity of compressed tomography, and almost-matching lower bounds on the sample complexity of any procedure using adaptive sequences of Pauli measurements. Using numerical simulations, we compare the performance of two compressed sensing estimators—the matrix Dantzig selector and the matrix Lasso—with standard maximum-likelihood estimation (MLE). We find that, given comparable experimental resources, the compressed sensing estimators consistently produce higher fidelity state reconstructions than MLE. In addition, the use of an incomplete set of measurements leads to faster classical processing with no loss of accuracy. Finally, we show how to certify the accuracy of a low-rank estimate using direct fidelity estimation, and describe a method for compressed quantum process tomography that works for processes with small Kraus rank and requires only Pauli eigenstate preparations

The use of importance sampling in a trial assessment to obtain converged estimates of radiological risk

International Nuclear Information System (INIS)

Johnson, K.; Lucas, R.

1986-12-01

In developing a methodology for assessing potential sites for the disposal of radioactive wastes, the Department of the Environment has conducted a series of trial assessment exercises. In order to produce converged estimates of radiological risk using the SYVAC A/C simulation system an efficient sampling procedure is required. Previous work has demonstrated that importance sampling can substantially increase sampling efficiency. This study used importance sampling to produce converged estimates of risk for the first DoE trial assessment. Four major nuclide chains were analysed. In each case importance sampling produced converged risk estimates with between 10 and 170 times fewer runs of the SYVAC A/C model. This increase in sampling efficiency can reduce the total elapsed time required to obtain a converged estimate of risk from one nuclide chain by a factor of 20. The results of this study suggests that the use of importance sampling could reduce the elapsed time required to perform a risk assessment of a potential site by a factor of ten. (author)

An efficient modularized sample-based method to estimate the first-order Sobol' index

International Nuclear Information System (INIS)

Li, Chenzhao; Mahadevan, Sankaran

2016-01-01

Sobol' index is a prominent methodology in global sensitivity analysis. This paper aims to directly estimate the Sobol' index based only on available input–output samples, even if the underlying model is unavailable. For this purpose, a new method to calculate the first-order Sobol' index is proposed. The innovation is that the conditional variance and mean in the formula of the first-order index are calculated at an unknown but existing location of model inputs, instead of an explicit user-defined location. The proposed method is modularized in two aspects: 1) index calculations for different model inputs are separate and use the same set of samples; and 2) model input sampling, model evaluation, and index calculation are separate. Due to this modularization, the proposed method is capable to compute the first-order index if only input–output samples are available but the underlying model is unavailable, and its computational cost is not proportional to the dimension of the model inputs. In addition, the proposed method can also estimate the first-order index with correlated model inputs. Considering that the first-order index is a desired metric to rank model inputs but current methods can only handle independent model inputs, the proposed method contributes to fill this gap. - Highlights: • An efficient method to estimate the first-order Sobol' index. • Estimate the index from input–output samples directly. • Computational cost is not proportional to the number of model inputs. • Handle both uncorrelated and correlated model inputs.

Respondent driven sampling: determinants of recruitment and a method to improve point estimation.

Directory of Open Access Journals (Sweden)

Nicky McCreesh

Full Text Available Respondent-driven sampling (RDS is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview.Using data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods, and also of presentation for interview if offered a coupon by age and socioeconomic status group.Younger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19-29%, but had little effect for sexual activity or HIV status.Data collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

Science.gov (United States)

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

A Model-Driven Approach for Hybrid Power Estimation in Embedded Systems Design

Directory of Open Access Journals (Sweden)

Ben Atitallah Rabie

2011-01-01

Full Text Available Abstract As technology scales for increased circuit density and performance, the management of power consumption in system-on-chip (SoC is becoming critical. Today, having the appropriate electronic system level (ESL tools for power estimation in the design flow is mandatory. The main challenge for the design of such dedicated tools is to achieve a better tradeoff between accuracy and speed. This paper presents a consumption estimation approach allowing taking the consumption criterion into account early in the design flow during the system cosimulation. The originality of this approach is that it allows the power estimation for both white-box intellectual properties (IPs using annotated power models and black-box IPs using standalone power estimators. In order to obtain accurate power estimates, our simulations were performed at the cycle-accurate bit-accurate (CABA level, using SystemC. To make our approach fast and not tedious for users, the simulated architectures, including standalone power estimators, were generated automatically using a model driven engineering (MDE approach. Both annotated power models and standalone power estimators can be used together to estimate the consumption of the same architecture, which makes them complementary. The simulation results showed that the power estimates given by both estimation techniques for a hardware component are very close, with a difference that does not exceed 0.3%. This proves that, even when the IP code is not accessible or not modifiable, our approach allows obtaining quite accurate power estimates that early in the design flow thanks to the automation offered by the MDE approach.

A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters

NARCIS (Netherlands)

Peng, Yijie; Fu, Michael C.; Hu, Jian Qiang; Heidergott, Bernd

In this paper, we propose a new unbiased stochastic derivative estimator in a framework that can handle discontinuous sample performances with structural parameters. This work extends the three most popular unbiased stochastic derivative estimators: (1) infinitesimal perturbation analysis (IPA), (2)

Sensitivity of postplanning target and OAR coverage estimates to dosimetric margin distribution sampling parameters.

Science.gov (United States)

Xu, Huijun; Gordon, J James; Siebers, Jeffrey V

2011-02-01

A dosimetric margin (DM) is the margin in a specified direction between a structure and a specified isodose surface, corresponding to a prescription or tolerance dose. The dosimetric margin distribution (DMD) is the distribution of DMs over all directions. Given a geometric uncertainty model, representing inter- or intrafraction setup uncertainties or internal organ motion, the DMD can be used to calculate coverage Q, which is the probability that a realized target or organ-at-risk (OAR) dose metric D, exceeds the corresponding prescription or tolerance dose. Postplanning coverage evaluation quantifies the percentage of uncertainties for which target and OAR structures meet their intended dose constraints. The goal of the present work is to evaluate coverage probabilities for 28 prostate treatment plans to determine DMD sampling parameters that ensure adequate accuracy for postplanning coverage estimates. Normally distributed interfraction setup uncertainties were applied to 28 plans for localized prostate cancer, with prescribed dose of 79.2 Gy and 10 mm clinical target volume to planning target volume (CTV-to-PTV) margins. Using angular or isotropic sampling techniques, dosimetric margins were determined for the CTV, bladder and rectum, assuming shift invariance of the dose distribution. For angular sampling, DMDs were sampled at fixed angular intervals w (e.g., w = 1 degree, 2 degrees, 5 degrees, 10 degrees, 20 degrees). Isotropic samples were uniformly distributed on the unit sphere resulting in variable angular increments, but were calculated for the same number of sampling directions as angular DMDs, and accordingly characterized by the effective angular increment omega eff. In each direction, the DM was calculated by moving the structure in radial steps of size delta (=0.1, 0.2, 0.5, 1 mm) until the specified isodose was crossed. Coverage estimation accuracy deltaQ was quantified as a function of the sampling parameters omega or omega eff and delta. The

Statistical inference for the additive hazards model under outcome-dependent sampling.

Science.gov (United States)

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Bridging the gaps between non-invasive genetic sampling and population parameter estimation

Science.gov (United States)

Francesca Marucco; Luigi Boitani; Daniel H. Pletscher; Michael K. Schwartz

2011-01-01

Reliable estimates of population parameters are necessary for effective management and conservation actions. The use of genetic data for capture­recapture (CR) analyses has become an important tool to estimate population parameters for elusive species. Strong emphasis has been placed on the genetic analysis of non-invasive samples, or on the CR analysis; however,...

Exact run length distribution of the double sampling x-bar chart with estimated process parameters

Directory of Open Access Journals (Sweden)

Teoh, W. L.

2016-05-01

Full Text Available Since the run length distribution is generally highly skewed, a significant concern about focusing too much on the average run length (ARL criterion is that we may miss some crucial information about a control chart’s performance. Thus it is important to investigate the entire run length distribution of a control chart for an in-depth understanding before implementing the chart in process monitoring. In this paper, the percentiles of the run length distribution for the double sampling (DS X chart with estimated process parameters are computed. Knowledge of the percentiles of the run length distribution provides a more comprehensive understanding of the expected behaviour of the run length. This additional information includes the early false alarm, the skewness of the run length distribution, and the median run length (MRL. A comparison of the run length distribution between the optimal ARL-based and MRL-based DS X chart with estimated process parameters is presented in this paper. Examples of applications are given to aid practitioners to select the best design scheme of the DS X chart with estimated process parameters, based on their specific purpose.

Estimating an appropriate sampling frequency for monitoring ground water well contamination

International Nuclear Information System (INIS)

Tuckfield, R.C.

1994-01-01

Nearly 1,500 ground water wells at the Savannah River Site (SRS) are sampled quarterly to monitor contamination by radionuclides and other hazardous constituents from nearby waste sites. Some 10,000 water samples were collected in 1993 at a laboratory analysis cost of $10,000,000. No widely accepted statistical method has been developed, to date, for estimating a technically defensible ground water sampling frequency consistent and compliant with federal regulations. Such a method is presented here based on the concept of statistical independence among successively measured contaminant concentrations in time

Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation.

Science.gov (United States)

Cheung, Chi Yuen; van der Heijden, Jaques; Hoogtanders, Karin; Christiaans, Maarten; Liu, Yan Lun; Chan, Yiu Han; Choi, Koon Shing; van de Plas, Afke; Shek, Chi Chung; Chau, Ka Foon; Li, Chun Sang; van Hooff, Johannes; Stolk, Leo

2008-02-01

Dried blood spot (DBS) sampling and high-performance liquid chromatography tandem-mass spectrometry have been developed in monitoring tacrolimus levels. Our center favors the use of limited sampling strategy and abbreviated formula to estimate the area under concentration-time curve (AUC(0-12)). However, it is inconvenient for patients because they have to wait in the center for blood sampling. We investigated the application of DBS method in tacrolimus level monitoring using limited sampling strategy and abbreviated AUC estimation approach. Duplicate venous samples were obtained at each time point (C(0), C(2), and C(4)). To determine the stability of blood samples, one venous sample was sent to our laboratory immediately. The other duplicate venous samples, together with simultaneous fingerprick blood samples, were sent to the University of Maastricht in the Netherlands. Thirty six patients were recruited and 108 sets of blood samples were collected. There was a highly significant relationship between AUC(0-12), estimated from venous blood samples, and fingerprick blood samples (r(2) = 0.96, P AUC(0-12) strategy as drug monitoring.

Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods

Science.gov (United States)

Gould, Matthew J.; Cain, James W.; Roemer, Gary W.; Gould, William R.

2016-01-01

samples. We identified 725 (367 M, 358 F) individuals; the sex ratio for each study area was approximately equal. Our density estimates varied within and among mountain ranges with an estimated density of 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) for the NSC, 19.74 bears/100 km2 (95% CI: 13.77 – 28.30) in the SSC, 25.75 bears/100 km2 (95% CI: 13.22 – 50.14) in the Sandias, 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) in the NSacs, and 16.55 bears/100 km2 (95% CI: 11.64 – 23.53) in the SSacs. Overall detection probability for hair traps and bear rubs, combined, was low across all study areas and ranged from 0.00001 to 0.02. We speculate that detection probabilities were affected by failure of some hair samples to produce a complete genotype due to UV degradation of DNA, and our inability to set and check some sampling devices due to wildfires in the SSC. Ultraviolet radiation levels are particularly high in New Mexico compared to other states where NGS methods have been used because New Mexico receives substantial amounts of sunshine, is relatively high in elevation (1,200 m – 4,000 m), and is at a lower latitude. Despite these sampling difficulties, we were able to produce density estimates for New Mexico black bear populations with levels of precision comparable to estimated black bear densities made elsewhere in the U.S.Our ability to generate reliable black bear density estimates for 3 New Mexico mountain ranges is attributable to our use of a statistically robust study design and analytical method. There are multiple factors that need to be considered when developing future SECR-based density estimation projects. First, the spatial extent of the population of interest and the smallest average home range size must be determined; these will dictate size of the trapping array and spacing necessary between hair traps. The number of technicians needed and access to the study areas will also influence configuration of the trapping array. We believe shorter

ANL small-sample calorimeter system design and operation

International Nuclear Information System (INIS)

Roche, C.T.; Perry, R.B.; Lewis, R.N.; Jung, E.A.; Haumann, J.R.

1978-07-01

The Small-Sample Calorimetric System is a portable instrument designed to measure the thermal power produced by radioactive decay of plutonium-containing fuels. The small-sample calorimeter is capable of measuring samples producing power up to 32 milliwatts at a rate of one sample every 20 min. The instrument is contained in two packages: a data-acquisition module consisting of a microprocessor with an 8K-byte nonvolatile memory, and a measurement module consisting of the calorimeter and a sample preheater. The total weight of the system is 18 kg

Baysian estimation of P(X > x) from a small sample of Gaussian data

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager

2017-01-01

The classical statistical uncertainty problem of estimation of upper tail probabilities on the basis of a small sample of observations of a Gaussian random variable is considered. Predictive posterior estimation is discussed, adopting the standard statistical model with diffuse priors of the two...

A Convenient Method for Estimation of the Isotopic Abundance in Uranium Bearing Samples

International Nuclear Information System (INIS)

AI -Saleh, F.S.; AI-Mukren, Alj.H.; Farouk, M.A.

2008-01-01

A convenient and simple method for estimation of the isotopic abundance in some uranium bearing samples using gamma-ray spectrometry is developed using a hyper pure germanium spectrometer and a standard uranium sample with known isotopic abundance

A rapid method for estimation of Pu-isotopes in urine samples using high volume centrifuge.

Science.gov (United States)

Kumar, Ranjeet; Rao, D D; Dubla, Rupali; Yadav, J R

2017-07-01

The conventional radio-analytical technique used for estimation of Pu-isotopes in urine samples involves anion exchange/TEVA column separation followed by alpha spectrometry. This sequence of analysis consumes nearly 3-4 days for completion. Many a times excreta analysis results are required urgently, particularly under repeat and incidental/emergency situations. Therefore, there is need to reduce the analysis time for the estimation of Pu-isotopes in bioassay samples. This paper gives the details of standardization of a rapid method for estimation of Pu-isotopes in urine samples using multi-purpose centrifuge, TEVA resin followed by alpha spectrometry. The rapid method involves oxidation of urine samples, co-precipitation of plutonium along with calcium phosphate followed by sample preparation using high volume centrifuge and separation of Pu using TEVA resin. Pu-fraction was electrodeposited and activity estimated using 236 Pu tracer recovery by alpha spectrometry. Ten routine urine samples of radiation workers were analyzed and consistent radiochemical tracer recovery was obtained in the range 47-88% with a mean and standard deviation of 64.4% and 11.3% respectively. With this newly standardized technique, the whole analytical procedure is completed within 9h (one working day hour). Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive designs for the one-sample log-rank test.

Science.gov (United States)

Schmidt, Rene; Faldum, Andreas; Kwiecien, Robert

2017-09-22

Traditional designs in phase IIa cancer trials are single-arm designs with a binary outcome, for example, tumor response. In some settings, however, a time-to-event endpoint might appear more appropriate, particularly in the presence of loss to follow-up. Then the one-sample log-rank test might be the method of choice. It allows to compare the survival curve of the patients under treatment to a prespecified reference survival curve. The reference curve usually represents the expected survival under standard of the care. In this work, convergence of the one-sample log-rank statistic to Brownian motion is proven using Rebolledo's martingale central limit theorem while accounting for staggered entry times of the patients. On this basis, a confirmatory adaptive one-sample log-rank test is proposed where provision is made for data dependent sample size reassessment. The focus is to apply the inverse normal method. This is done in two different directions. The first strategy exploits the independent increments property of the one-sample log-rank statistic. The second strategy is based on the patient-wise separation principle. It is shown by simulation that the proposed adaptive test might help to rescue an underpowered trial and at the same time lowers the average sample number (ASN) under the null hypothesis as compared to a single-stage fixed sample design. © 2017, The International Biometric Society.

Robust experiment design for estimating myocardial β adrenergic receptor concentration using PET

International Nuclear Information System (INIS)

Salinas, Cristian; Muzic, Raymond F. Jr.; Ernsberger, Paul; Saidel, Gerald M.

2007-01-01

Myocardial β adrenergic receptor (β-AR) concentration can substantially decrease in congestive heart failure and significantly increase in chronic volume overload, such as in severe aortic valve regurgitation. Positron emission tomography (PET) with an appropriate ligand-receptor model can be used for noninvasive estimation of myocardial β-AR concentration in vivo. An optimal design of the experiment protocol, however, is needed for sufficiently precise estimates of β-AR concentration in a heterogeneous population. Standard methods of optimal design do not account for a heterogeneous population with a wide range of β-AR concentrations and other physiological parameters and consequently are inadequate. To address this, we have developed a methodology to design a robust two-injection protocol that provides reliable estimates of myocardial β-AR concentration in normal and pathologic states. A two-injection protocol of the high affinity β-AR antagonist [ 18 F]-(S)-fluorocarazolol was designed based on a computer-generated (or synthetic) population incorporating a wide range of β-AR concentrations. Timing and dosage of the ligand injections were optimally designed with minimax criterion to provide the least bad β-AR estimates for the worst case in the synthetic population. This robust experiment design for PET was applied to experiments with pigs before and after β-AR upregulation by chemical sympathectomy. Estimates of β-AR concentration were found by minimizing the difference between the model-predicted and experimental PET data. With this robust protocol, estimates of β-AR concentration showed high precision in both normal and pathologic states. The increase in β-AR concentration after sympathectomy predicted noninvasively with PET is consistent with the increase shown by in vitro assays in pig myocardium. A robust experiment protocol was designed for PET that yields reliable estimates of β-AR concentration in a population with normal and pathologic

Environmental DNA (eDNA sampling improves occurrence and detection estimates of invasive burmese pythons.

Directory of Open Access Journals (Sweden)

Margaret E Hunter

Full Text Available Environmental DNA (eDNA methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR for the Burmese python (Python molurus bivittatus, Northern African python (P. sebae, boa constrictor (Boa constrictor, and the green (Eunectes murinus and yellow anaconda (E. notaeus. Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive

Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive burmese pythons.

Science.gov (United States)

Hunter, Margaret E; Oyler-McCance, Sara J; Dorazio, Robert M; Fike, Jennifer A; Smith, Brian J; Hunter, Charles T; Reed, Robert N; Hart, Kristen M

2015-01-01

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors

Baseline Design Compliance Matrix for the Rotary Mode Core Sampling System

International Nuclear Information System (INIS)

LECHELT, J.A.

2000-01-01

The purpose of the design compliance matrix (DCM) is to provide a single-source document of all design requirements associated with the fifteen subsystems that make up the rotary mode core sampling (RMCS) system. It is intended to be the baseline requirement document for the RMCS system and to be used in governing all future design and design verification activities associated with it. This document is the DCM for the RMCS system used on Hanford single-shell radioactive waste storage tanks. This includes the Exhauster System, Rotary Mode Core Sample Trucks, Universal Sampling System, Diesel Generator System, Distribution Trailer, X-Ray Cart System, Breathing Air Compressor, Nitrogen Supply Trailer, Casks and Cask Truck, Service Trailer, Core Sampling Riser Equipment, Core Sampling Support Trucks, Foot Clamp, Ramps and Platforms and Purged Camera System. Excluded items are tools such as light plants and light stands. Other items such as the breather inlet filter are covered by a different design baseline. In this case, the inlet breather filter is covered by the Tank Farms Design Compliance Matrix

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

Science.gov (United States)

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Application of Singh et al., unbiased estimator in a dual to ratio-cum ...

African Journals Online (AJOL)

This paper applied an unbiased estimator in a dual to ratio–cum-product estimator in sample surveys to double sampling design. Its efficiency over the conventional biased double sampling design estimator was determined based on the conditions attached to its supremacy. Three different data sets were used to testify to ...

Within-otolith variability in chemical fingerprints: implications for sampling designs and possible environmental interpretation.

Directory of Open Access Journals (Sweden)

Antonio Di Franco

Full Text Available Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS. LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1 whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2 the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast. We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within

Within-otolith variability in chemical fingerprints: implications for sampling designs and possible environmental interpretation.

Science.gov (United States)

Di Franco, Antonio; Bulleri, Fabio; Pennetta, Antonio; De Benedetto, Giuseppe; Clarke, K Robert; Guidetti, Paolo

2014-01-01

Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the

Top-down and bottom-up approaches for cost estimating new reactor designs

International Nuclear Information System (INIS)

Berbey, P.; Gautier, G.M.; Duflo, D.; Rouyer, J.L.

2007-01-01

For several years, Generation-4 designs will be 'pre-conceptual' for the less mature concepts and 'preliminary' for the more mature concepts. In this situation, appropriate data for some of the plant systems may be lacking to develop a bottom-up cost estimate. Therefore, a more global approach, the Top-Down Approach (TDA), is needed to help the designers and decision makers in comparing design options. It utilizes more or less simple models for cost estimating the different parts of a design. TDA cost estimating effort applies to a whole functional element whose cost is approached by similar estimations coming from existing data, ratios and models, for a given range of variation of parameters. Modeling is used when direct analogy is not possible. There are two types of models, global and specific ones. Global models are applied to cost modules related to Code Of Account. Exponential formulae such as Ci = Ai + (Bi x Pi n ) are used when there are cost data for comparable modules in nuclear or other industries. Specific cost models are developed for major specific components of the plant: - process equipment such as reactor vessel, steam generators or large heat exchangers. - buildings, with formulae estimating the construction cost from base cost of m3 of building volume. - systems, when unit costs, cost ratios and models are used, depending on the level of detail of the design. Bottom Up Approach (BUA), which is based on unit prices coming from similar equipment or from manufacturer consulting, is very valuable and gives better cost estimations than TDA when it can be applied, that is at a rather late stage of the design. Both approaches are complementary when some parts of the design are detailed enough to be estimated by BUA, and when BUA results are used to check TDA results and to improve TDA models. This methodology is applied to the HTR (High Temperature Reactor) concept and to an advanced PWR design

Estimation of uranium isotope in urine samples using extraction chromatography resin

International Nuclear Information System (INIS)

Thakur, Smita S.; Yadav, J.R.; Rao, D.D.

2012-01-01

Internal exposure monitoring for alpha emitting radionuclides is carried out by bioassay samples analysis. For occupational radiation workers handling uranium in reprocessing or fuel fabrication facilities, there exists a possibility of internal exposure and urine assay is the preferred method for monitoring such exposure. Estimation of lower concentration of uranium at mBq level by alpha spectrometry requires preconcentration and its separation from large volume of urine sample. For this purpose, urine samples collected from non radiation workers were spiked with 232 U tracer at mBq level to estimate the chemical yield. Uranium in urine sample was pre-concentrated by calcium phosphate coprecipitation and separated by extraction chromatography resin U/TEVA. In this resin extractant was DAAP (Diamylamylphosphonate) supported on inert Amberlite XAD-7 support material. After co-precipitation, precipitate was centrifuged and dissolved in 10 ml of 1M Al(NO 3 ) 3 prepared in 3M HNO 3 . The sample thus prepared was loaded on extraction chromatography resin, pre-conditioned with 10 ml of 3M HNO 3 . Column was washed with 10 ml of 3M HNO 3 . Column was again rinsed with 5 ml of 9M HCl followed by 20 ml of 0.05 M oxalic acid prepared in 5M HCl to remove interference due to Th and Np if present in the sample. Uranium was eluted from U/TEVA column with 15 ml of 0.01M HCl. The eluted uranium fraction was electrodeposited on stainless steel planchet and counted by alpha spectrometry for 360000 sec. Approximate analysis time involved from sample loading to stripping is 2 hours when compared with the time involved of 3.5 hours by conventional ion exchange method. Seven urine samples from non radiation worker were radio chemically analyzed by this technique and the radiochemical yield was found in the range of 69-91 %. Efficacy of this method against conventional anion exchange technique earlier standardized at this laboratory is also being highlighted. Minimum detectable activity

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

OpenAIRE

Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

2014-01-01

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in ...

Development of a customised design flood estimation tool to ...

African Journals Online (AJOL)

The estimation of design flood events, i.e., floods characterised by a specific magnitude-frequency relationship, at a particular site in a specific region is necessary for the planning, design and operation of hydraulic structures. Both the occurrence and frequency of flood events, along with the uncertainty involved in the ...

Near-native protein loop sampling using nonparametric density estimation accommodating sparcity.

Science.gov (United States)

Joo, Hyun; Chavan, Archana G; Day, Ryan; Lennox, Kristin P; Sukhanov, Paul; Dahl, David B; Vannucci, Marina; Tsai, Jerry

2011-10-01

Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD 7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.

Near-native protein loop sampling using nonparametric density estimation accommodating sparcity.

Directory of Open Access Journals (Sweden)

Hyun Joo

2011-10-01

Full Text Available Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM. Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD 7.0 Å, this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.

Near-Native Protein Loop Sampling Using Nonparametric Density Estimation Accommodating Sparcity

Science.gov (United States)

Day, Ryan; Lennox, Kristin P.; Sukhanov, Paul; Dahl, David B.; Vannucci, Marina; Tsai, Jerry

2011-01-01

Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD 7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/. PMID:22028638

Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.

Science.gov (United States)

Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko

2017-06-01

Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.

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)

Establishing a cost model when estimating product cost in early design phases

OpenAIRE

Jeppsson, Johanna; Sjöberg, Jessica

2017-01-01

About 75% of the total product cost is determined in the early design phase, which means that the possibilities to affect costs are relatively small when the design phase is completed. For companies, it is therefore vital to conduct reliable cost estimates in the early design phase, when selecting between different design choices. When conducting a cost estimate there are many uncertainties. The aim with this study is therefore to explore how uncertainties regarding product cost can be consid...

A Frequency Domain Design Method For Sampled-Data Compensators

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Jannerup, Ole Erik

1990-01-01

A new approach to the design of a sampled-data compensator in the frequency domain is investigated. The starting point is a continuous-time compensator for the continuous-time system which satisfy specific design criteria. The new design method will graphically show how the discrete...

On-line estimator/detector design for a plutonium nitrate concentrator unit

International Nuclear Information System (INIS)

Candy, J.V.; Rozsa, R.B.

1979-04-01

In this report we consider the design of a nonlinear estimator to be used in conjunction with on-line detectors for a plutonium/concentrator. Using a complex state-of-the-art process model to simulate realistic data, we show that the estimator performance using a simplified process model is adequate over a wide range of operation. The estimator is used to simulate and characterize some on-line diversion detectors, i.e., detectors designed to indicate if some of the critical special nuclear material in process is stolen or diverted from the unit. Several different diversion scenarios are presented. Simulation results indicate that the estimators and detectors yielded reasonable performance for the scenarios investigated

A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

Science.gov (United States)

Boyd, James H; Guiver, Tenniel; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Anderson, Phil; Dickinson, Teresa

2016-05-17

Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives. The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage. In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known. The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601). This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.

Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization

OpenAIRE

Trevelin, Leonardo Carreira; Novaes, Roberto Leonan Morim; Colas-Rosas, Paul François; Benathar, Thayse Cristhina Melo; Peres, Carlos A.

2017-01-01

The advantages of mist-netting, the main technique used in Neotropical bat community studies to date, include logistical implementation, standardization and sampling representativeness. Nonetheless, study designs still have to deal with issues of detectability related to how different species behave and use the environment. Yet there is considerable sampling heterogeneity across available studies in the literature. Here, we approach the problem of sample size optimization. We evaluated the co...

Design and analysis of control charts for standard deviation with estimated parameters

NARCIS (Netherlands)

Schoonhoven, M.; Riaz, M.; Does, R.J.M.M.

2011-01-01

This paper concerns the design and analysis of the standard deviation control chart with estimated limits. We consider an extensive range of statistics to estimate the in-control standard deviation (Phase I) and design the control chart for real-time process monitoring (Phase II) by determining the

Sample design and gamma-ray counting strategy of neutron activation system for triton burnup measurements in KSTAR

Energy Technology Data Exchange (ETDEWEB)

Jo, Jungmin [Department of Energy System Engineering, Seoul National University, Seoul (Korea, Republic of); Cheon, Mun Seong [ITER Korea, National Fusion Research Institute, Daejeon (Korea, Republic of); Chung, Kyoung-Jae, E-mail: jkjlsh1@snu.ac.kr [Department of Energy System Engineering, Seoul National University, Seoul (Korea, Republic of); Hwang, Y.S. [Department of Energy System Engineering, Seoul National University, Seoul (Korea, Republic of)

2016-11-01

Highlights: • Sample design for triton burnup ratio measurement is carried out. • Samples for 14.1 MeV neutron measurements are selected for KSTAR. • Si and Cu are the most suitable materials for d-t neutron measurements. • Appropriate γ-ray counting strategies for each selected sample are established. - Abstract: On the purpose of triton burnup measurements in Korea Superconducting Tokamak Advanced Research (KSTAR) deuterium plasmas, appropriate neutron activation system (NAS) samples for 14.1 MeV d-t neutron measurements have been designed and gamma-ray counting strategy is established. Neutronics calculations are performed with the MCNP5 neutron transport code for the KSTAR neutral beam heated deuterium plasma discharges. Based on those calculations and the assumed d-t neutron yield, the activities induced by d-t neutrons are estimated with the inventory code FISPACT-2007 for candidate sample materials: Si, Cu, Al, Fe, Nb, Co, Ti, and Ni. It is found that Si, Cu, Al, and Fe are suitable for the KSATR NAS in terms of the minimum detectable activity (MDA) calculated based on the standard deviation of blank measurements. Considering background gamma-rays radiated from surrounding structures activated by thermalized fusion neutrons, appropriate gamma-ray counting strategy for each selected sample is established.

The PowerAtlas: a power and sample size atlas for microarray experimental design and research

Directory of Open Access Journals (Sweden)

Wang Jelai

2006-02-01

Full Text Available Abstract Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas 1. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO. The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC. Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.

Estimation of uranium in different types of water and sand samples by adsorptive stripping voltammetry

International Nuclear Information System (INIS)

Bhalke, Sunil; Raghunath, Radha; Mishra, Suchismita; Suseela, B.; Tripathi, R.M.; Pandit, G.G.; Shukla, V.K.; Puranik, V.D.

2005-01-01

A method is standardized for the estimation of uranium by adsorptive stripping voltammetry using chloranilic acid (CAA) as complexing agent. The optimum parameters to get best sensitivity and good reproducibility for uranium were 60s adsorption time, pH 1.8, chloranilic acid (2x10 -4 M) and 0.002M EDTA. The peak potential under this condition was found to be -0.03 V. With these optimum parameters a sensitivity of 1.19 nA/nM uranium was observed. Detection limit for this optimum parameter was found to be 0.55 nM. This can be further improved by increasing adsorption time. Using this method, uranium was estimated in different type of water samples such as seawater, synthetic seawater, stream water, tap water, well water, bore well water and process water. This method has also been used for estimation of uranium in sand, organic solvent used for extraction of uranium from phosphoric acid and its raffinate. Sample digestion procedures used for estimation of uranium in various matrices are discussed. It has been observed from the analysis that the uranium peak potentials changes with matrix of the sample, hence, standard addition method is the best method to get reliable and accurate results. Quality assurance of the standardized method is verified by analyzing certified reference water sample from USDOE, participating intercomparison exercises and also by estimating uranium content in water samples both by differential pulse adsorptive stripping voltammetric and laser fluorimetric techniques. (author)

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

Science.gov (United States)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

Methods for design flood estimation in South Africa

African Journals Online (AJOL)

2012-07-04

Jul 4, 2012 ... 1970s and are in need of updating with more than 40 years of additional data ... This paper reviews methods used for design flood estimation in South Africa and .... transposition of past experience, or a deterministic approach,.

Per tree estimates with n-tree distance sampling: an application to increment core data

Science.gov (United States)

Thomas B. Lynch; Robert F. Wittwer

2002-01-01

Per tree estimates using the n trees nearest a point can be obtained by using a ratio of per unit area estimates from n-tree distance sampling. This ratio was used to estimate average age by d.b.h. classes for cottonwood trees (Populus deltoides Bartr. ex Marsh.) on the Cimarron National Grassland. Increment...

An empirical analysis of the precision of estimating the numbers of neurons and glia in human neocortex using a fractionator-design with sub-sampling

DEFF Research Database (Denmark)

Lyck, L.; Santamaria, I.D.; Pakkenberg, B.

2009-01-01

Improving histomorphometric analysis of the human neocortex by combining stereological cell counting with immunchistochemical visualisation of specific neuronal and glial cell populations is a methodological challenge. To enable standardized immunohistochemical staining, the amount of brain tissue...... at each level of sampling was determined empirically. The methodology was tested in three brains analysing the contribution of the multi-step sampling procedure to the precision on the estimated total numbers of immunohistochemically defined NeuN expressing (NeuN(+)) neurons and CD45(+) microglia...

Sample design considerations of indoor air exposure surveys

International Nuclear Information System (INIS)

Cox, B.G.; Mage, D.T.; Immerman, F.W.

1988-01-01

Concern about the potential for indoor air pollution has prompted recent surveys of radon and NO 2 concentrations in homes and personal exposure studies of volatile organics, carbon monoxide and pesticides, to name a few. The statistical problems in designing sample surveys that measure the physical environment are diverse and more complicated than those encountered in traditional surveys of human attitudes and attributes. This paper addresses issues encountered when designing indoor air quality (IAQ) studies. General statistical concepts related to target population definition, frame creation, and sample selection for area household surveys and telephone surveys are presented. The implications of different measurement approaches are discussed, and response rate considerations are described

Evaluation of species richness estimators based on quantitative performance measures and sensitivity to patchiness and sample grain size

Science.gov (United States)

Willie, Jacob; Petre, Charles-Albert; Tagg, Nikki; Lens, Luc

2012-11-01

Data from forest herbaceous plants in a site of known species richness in Cameroon were used to test the performance of rarefaction and eight species richness estimators (ACE, ICE, Chao1, Chao2, Jack1, Jack2, Bootstrap and MM). Bias, accuracy, precision and sensitivity to patchiness and sample grain size were the evaluation criteria. An evaluation of the effects of sampling effort and patchiness on diversity estimation is also provided. Stems were identified and counted in linear series of 1-m2 contiguous square plots distributed in six habitat types. Initially, 500 plots were sampled in each habitat type. The sampling process was monitored using rarefaction and a set of richness estimator curves. Curves from the first dataset suggested adequate sampling in riparian forest only. Additional plots ranging from 523 to 2143 were subsequently added in the undersampled habitats until most of the curves stabilized. Jack1 and ICE, the non-parametric richness estimators, performed better, being more accurate and less sensitive to patchiness and sample grain size, and significantly reducing biases that could not be detected by rarefaction and other estimators. This study confirms the usefulness of non-parametric incidence-based estimators, and recommends Jack1 or ICE alongside rarefaction while describing taxon richness and comparing results across areas sampled using similar or different grain sizes. As patchiness varied across habitat types, accurate estimations of diversity did not require the same number of plots. The number of samples needed to fully capture diversity is not necessarily the same across habitats, and can only be known when taxon sampling curves have indicated adequate sampling. Differences in observed species richness between habitats were generally due to differences in patchiness, except between two habitats where they resulted from differences in abundance. We suggest that communities should first be sampled thoroughly using appropriate taxon sampling

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

Science.gov (United States)

Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

2012-10-12

Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

Development of Property Models with Uncertainty Estimate for Process Design under Uncertainty

DEFF Research Database (Denmark)

Hukkerikar, Amol; Sarup, Bent; Abildskov, Jens

more reliable predictions with a new and improved set of model parameters for GC (group contribution) based and CI (atom connectivity index) based models and to quantify the uncertainties in the estimated property values from a process design point-of-view. This includes: (i) parameter estimation using....... The comparison of model prediction uncertainties with reported range of measurement uncertainties is presented for the properties with related available data. The application of the developed methodology to quantify the effect of these uncertainties on the design of different unit operations (distillation column......, the developed methodology can be used to quantify the sensitivity of process design to uncertainties in property estimates; obtain rationally the risk/safety factors in process design; and identify additional experimentation needs in order to reduce most critical uncertainties....

A sampling strategy for estimating plot average annual fluxes of chemical elements from forest soils

NARCIS (Netherlands)

Brus, D.J.; Gruijter, de J.J.; Vries, de W.

2010-01-01

A sampling strategy for estimating spatially averaged annual element leaching fluxes from forest soils is presented and tested in three Dutch forest monitoring plots. In this method sampling locations and times (days) are selected by probability sampling. Sampling locations were selected by

Lagoa Real design. Description and evaluation of sampling system

International Nuclear Information System (INIS)

Hashizume, B.K.

1982-10-01

This report describes the samples preparation system of drilling from Lagoa Real Design, aiming obtainment representative fraction of the half from drilling outlier. The error of sampling + analysis and analytical accuracy was obtainment by delayed neutron analysis. (author)

Method for estimating modulation transfer function from sample images.

Science.gov (United States)

Saiga, Rino; Takeuchi, Akihisa; Uesugi, Kentaro; Terada, Yasuko; Suzuki, Yoshio; Mizutani, Ryuta

2018-02-01

The modulation transfer function (MTF) represents the frequency domain response of imaging modalities. Here, we report a method for estimating the MTF from sample images. Test images were generated from a number of images, including those taken with an electron microscope and with an observation satellite. These original images were convolved with point spread functions (PSFs) including those of circular apertures. The resultant test images were subjected to a Fourier transformation. The logarithm of the squared norm of the Fourier transform was plotted against the squared distance from the origin. Linear correlations were observed in the logarithmic plots, indicating that the PSF of the test images can be approximated with a Gaussian. The MTF was then calculated from the Gaussian-approximated PSF. The obtained MTF closely coincided with the MTF predicted from the original PSF. The MTF of an x-ray microtomographic section of a fly brain was also estimated with this method. The obtained MTF showed good agreement with the MTF determined from an edge profile of an aluminum test object. We suggest that this approach is an alternative way of estimating the MTF, independently of the image type. Copyright © 2017 Elsevier Ltd. All rights reserved.

Perception-oriented methodology for robust motion estimation design

NARCIS (Netherlands)

Heinrich, A.; Vleuten, van der R.J.; Haan, de G.

2014-01-01

Optimizing a motion estimator (ME) for picture rate conversion is challenging. This is because there are many types of MEs and, within each type, many parameters, which makes subjective assessment of all the alternatives impractical. To solve this problem, we propose an automatic design methodology

A novel recursive Fourier transform for nonuniform sampled signals: application to heart rate variability spectrum estimation.

Science.gov (United States)

Holland, Alexander; Aboy, Mateo

2009-07-01

We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability. We compare RFT based spectrum estimation with Lomb-Scargle Transform (LST) based estimation. PSD estimation based on the LST also does not require uniform time samples, but the LST has a computational order greater than Nlog(N). We conducted an assessment study involving the analysis of quasi-stationary signals with various levels of randomly missing heart beats. Our results indicate that the RFT leads to comparable estimation performance to the LST with significantly less computational overhead and complexity for applications requiring iterative spectrum estimations.

PERIOD ESTIMATION FOR SPARSELY SAMPLED QUASI-PERIODIC LIGHT CURVES APPLIED TO MIRAS

Energy Technology Data Exchange (ETDEWEB)

He, Shiyuan; Huang, Jianhua Z.; Long, James [Department of Statistics, Texas A and M University, College Station, TX (United States); Yuan, Wenlong; Macri, Lucas M., E-mail: lmacri@tamu.edu [George P. and Cynthia W. Mitchell Institute for Fundamental Physics and Astronomy, Department of Physics and Astronomy, Texas A and M University, College Station, TX (United States)

2016-12-01

We develop a nonlinear semi-parametric Gaussian process model to estimate periods of Miras with sparsely sampled light curves. The model uses a sinusoidal basis for the periodic variation and a Gaussian process for the stochastic changes. We use maximum likelihood to estimate the period and the parameters of the Gaussian process, while integrating out the effects of other nuisance parameters in the model with respect to a suitable prior distribution obtained from earlier studies. Since the likelihood is highly multimodal for period, we implement a hybrid method that applies the quasi-Newton algorithm for Gaussian process parameters and search the period/frequency parameter space over a dense grid. A large-scale, high-fidelity simulation is conducted to mimic the sampling quality of Mira light curves obtained by the M33 Synoptic Stellar Survey. The simulated data set is publicly available and can serve as a testbed for future evaluation of different period estimation methods. The semi-parametric model outperforms an existing algorithm on this simulated test data set as measured by period recovery rate and quality of the resulting period–luminosity relations.

Estimation of salt intake from spot urine samples in patients with chronic kidney disease

Directory of Open Access Journals (Sweden)

Ogura Makoto

2012-06-01

Full Text Available Abstract Background High salt intake in patients with chronic kidney disease (CKD may cause high blood pressure and increased albuminuria. Although, the estimation of salt intake is essential, there are no easy methods to estimate real salt intake. Methods Salt intake was assessed by determining urinary sodium excretion from the collected urine samples. Estimation of salt intake by spot urine was calculated by Tanaka’s formula. The correlation between estimated and measured sodium excretion was evaluated by Pearson´s correlation coefficients. Performance of equation was estimated by median bias, interquartile range (IQR, proportion of estimates within 30% deviation of measured sodium excretion (P30 and root mean square error (RMSE.The sensitivity and specificity of estimated against measured sodium excretion were separately assessed by receiver-operating characteristic (ROC curves. Results A total of 334 urine samples from 96 patients were examined. Mean age was 58 ± 16 years, and estimated glomerular filtration rate (eGFR was 53 ± 27 mL/min. Among these patients, 35 had CKD stage 1 or 2, 39 had stage 3, and 22 had stage 4 or 5. Estimated sodium excretion significantly correlated with measured sodium excretion (R = 0.52, P 170 mEq/day (AUC 0.835. Conclusions The present study demonstrated that spot urine can be used to estimate sodium excretion, especially in patients with low eGFR.

Bayesian approach to estimate AUC, partition coefficient and drug targeting index for studies with serial sacrifice design.

Science.gov (United States)

Wang, Tianli; Baron, Kyle; Zhong, Wei; Brundage, Richard; Elmquist, William

2014-03-01

The current study presents a Bayesian approach to non-compartmental analysis (NCA), which provides the accurate and precise estimate of AUC 0 (∞) and any AUC 0 (∞) -based NCA parameter or derivation. In order to assess the performance of the proposed method, 1,000 simulated datasets were generated in different scenarios. A Bayesian method was used to estimate the tissue and plasma AUC 0 (∞) s and the tissue-to-plasma AUC 0 (∞) ratio. The posterior medians and the coverage of 95% credible intervals for the true parameter values were examined. The method was applied to laboratory data from a mice brain distribution study with serial sacrifice design for illustration. Bayesian NCA approach is accurate and precise in point estimation of the AUC 0 (∞) and the partition coefficient under a serial sacrifice design. It also provides a consistently good variance estimate, even considering the variability of the data and the physiological structure of the pharmacokinetic model. The application in the case study obtained a physiologically reasonable posterior distribution of AUC, with a posterior median close to the value estimated by classic Bailer-type methods. This Bayesian NCA approach for sparse data analysis provides statistical inference on the variability of AUC 0 (∞) -based parameters such as partition coefficient and drug targeting index, so that the comparison of these parameters following destructive sampling becomes statistically feasible.

Automated CBED processing: Sample thickness estimation based on analysis of zone-axis CBED pattern

Energy Technology Data Exchange (ETDEWEB)

Klinger, M., E-mail: klinger@post.cz; Němec, M.; Polívka, L.; Gärtnerová, V.; Jäger, A.

2015-03-15

An automated processing of convergent beam electron diffraction (CBED) patterns is presented. The proposed methods are used in an automated tool for estimating the thickness of transmission electron microscopy (TEM) samples by matching an experimental zone-axis CBED pattern with a series of patterns simulated for known thicknesses. The proposed tool detects CBED disks, localizes a pattern in detected disks and unifies the coordinate system of the experimental pattern with the simulated one. The experimental pattern is then compared disk-by-disk with a series of simulated patterns each corresponding to different known thicknesses. The thickness of the most similar simulated pattern is then taken as the thickness estimate. The tool was tested on [0 1 1] Si, [0 1 0] α-Ti and [0 1 1] α-Ti samples prepared using different techniques. Results of the presented approach were compared with thickness estimates based on analysis of CBED patterns in two beam conditions. The mean difference between these two methods was 4.1% for the FIB-prepared silicon samples, 5.2% for the electro-chemically polished titanium and 7.9% for Ar{sup +} ion-polished titanium. The proposed techniques can also be employed in other established CBED analyses. Apart from the thickness estimation, it can potentially be used to quantify lattice deformation, structure factors, symmetry, defects or extinction distance. - Highlights: • Automated TEM sample thickness estimation using zone-axis CBED is presented. • Computer vision and artificial intelligence are employed in CBED processing. • This approach reduces operator effort, analysis time and increases repeatability. • Individual parts can be employed in other analyses of CBED/diffraction pattern.

Design review report for rotary mode core sample truck (RMCST) modifications for flammable gas tanks, preliminary design

International Nuclear Information System (INIS)

Corbett, J.E.

1996-02-01

This report documents the completion of a preliminary design review for the Rotary Mode Core Sample Truck (RMCST) modifications for flammable gas tanks. The RMCST modifications are intended to support core sampling operations in waste tanks requiring flammable gas controls. The objective of this review was to validate basic design assumptions and concepts to support a path forward leading to a final design. The conclusion reached by the review committee was that the design was acceptable and efforts should continue toward a final design review

Reliable Quantification of the Potential for Equations Based on Spot Urine Samples to Estimate Population Salt Intake

DEFF Research Database (Denmark)

Huang, Liping; Crino, Michelle; Wu, Jason Hy

2016-01-01

to a standard format. Individual participant records will be compiled and a series of analyses will be completed to: (1) compare existing equations for estimating 24-hour salt intake from spot urine samples with 24-hour urine samples, and assess the degree of bias according to key demographic and clinical......BACKGROUND: Methods based on spot urine samples (a single sample at one time-point) have been identified as a possible alternative approach to 24-hour urine samples for determining mean population salt intake. OBJECTIVE: The aim of this study is to identify a reliable method for estimating mean...... population salt intake from spot urine samples. This will be done by comparing the performance of existing equations against one other and against estimates derived from 24-hour urine samples. The effects of factors such as ethnicity, sex, age, body mass index, antihypertensive drug use, health status...

Sampling in ecology and evolution - bridging the gap between theory and practice

Science.gov (United States)

Albert, C.H.; Yoccoz, N.G.; Edwards, T.C.; Graham, C.H.; Zimmermann, N.E.; Thuiller, W.

2010-01-01

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi-virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response-surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model-based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of

Mechanical design and simulation of an automatized sample exchanger

International Nuclear Information System (INIS)

Lopez, Yon; Gora, Jimmy; Bedregal, Patricia; Hernandez, Yuri; Baltuano, Oscar; Gago, Javier

2013-01-01

The design of a turntable type sample exchanger for irradiation and with a capacity for up to 20 capsules was performed. Its function is the automatic sending of samples contained in polyethylene capsules, for irradiation in the grid position of the reactor core, using a pneumatic system and further analysis by neutron activation. This study shows the structural design analysis and calculations in selecting motors and actuators. This development will improve efficiency in the analysis, reducing the contribution of the workers and also the radiation exposure time. (authors).

Automatic sampling for unbiased and efficient stereological estimation using the proportionator in biological studies

DEFF Research Database (Denmark)

Gardi, Jonathan Eyal; Nyengaard, Jens Randel; Gundersen, Hans Jørgen Gottlieb

2008-01-01

Quantification of tissue properties is improved using the general proportionator sampling and estimation procedure: automatic image analysis and non-uniform sampling with probability proportional to size (PPS). The complete region of interest is partitioned into fields of view, and every field...... of view is given a weight (the size) proportional to the total amount of requested image analysis features in it. The fields of view sampled with known probabilities proportional to individual weight are the only ones seen by the observer who provides the correct count. Even though the image analysis...... cerebellum, total number of orexin positive neurons in transgenic mice brain, and estimating the absolute area and the areal fraction of β islet cells in dog pancreas.  The proportionator was at least eight times more efficient (precision and time combined) than traditional computer controlled sampling....

Implications of Clinical Trial Design on Sample Size Requirements

OpenAIRE

Leon, Andrew C.

2008-01-01

The primary goal in designing a randomized controlled clinical trial (RCT) is to minimize bias in the estimate of treatment effect. Randomized group assignment, double-blinded assessments, and control or comparison groups reduce the risk of bias. The design must also provide sufficient statistical power to detect a clinically meaningful treatment effect and maintain a nominal level of type I error. An attempt to integrate neurocognitive science into an RCT poses additional challenges. Two par...

Improving the accuracy of livestock distribution estimates through spatial interpolation.

Science.gov (United States)

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level

Effects of sample size on estimation of rainfall extremes at high temperatures

Science.gov (United States)

Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik

2017-09-01

High precipitation quantiles tend to rise with temperature, following the so-called Clausius-Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

Effects of sample size on estimation of rainfall extremes at high temperatures

Directory of Open Access Journals (Sweden)

B. Boessenkool

2017-09-01

Full Text Available High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali

Directory of Open Access Journals (Sweden)

Minetti Andrea

2012-10-01

Full Text Available Abstract Background Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS approach has been proposed as an alternative, as smaller sample sizes are required. Methods We explored (i the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. Results VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i health areas not requiring supplemental activities; ii health areas requiring additional vaccination; iii health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3, standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Conclusions Small sample cluster surveys (10 × 15 are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

Evaluating the accuracy of sampling to estimate central line-days: simplification of the National Healthcare Safety Network surveillance methods.

Science.gov (United States)

Thompson, Nicola D; Edwards, Jonathan R; Bamberg, Wendy; Beldavs, Zintars G; Dumyati, Ghinwa; Godine, Deborah; Maloney, Meghan; Kainer, Marion; Ray, Susan; Thompson, Deborah; Wilson, Lucy; Magill, Shelley S

2013-03-01

To evaluate the accuracy of weekly sampling of central line-associated bloodstream infection (CLABSI) denominator data to estimate central line-days (CLDs). Obtained CLABSI denominator logs showing daily counts of patient-days and CLD for 6-12 consecutive months from participants and CLABSI numerators and facility and location characteristics from the National Healthcare Safety Network (NHSN). Convenience sample of 119 inpatient locations in 63 acute care facilities within 9 states participating in the Emerging Infections Program. Actual CLD and estimated CLD obtained from sampling denominator data on all single-day and 2-day (day-pair) samples were compared by assessing the distributions of the CLD percentage error. Facility and location characteristics associated with increased precision of estimated CLD were assessed. The impact of using estimated CLD to calculate CLABSI rates was evaluated by measuring the change in CLABSI decile ranking. The distribution of CLD percentage error varied by the day and number of days sampled. On average, day-pair samples provided more accurate estimates than did single-day samples. For several day-pair samples, approximately 90% of locations had CLD percentage error of less than or equal to ±5%. A lower number of CLD per month was most significantly associated with poor precision in estimated CLD. Most locations experienced no change in CLABSI decile ranking, and no location's CLABSI ranking changed by more than 2 deciles. Sampling to obtain estimated CLD is a valid alternative to daily data collection for a large proportion of locations. Development of a sampling guideline for NHSN users is underway.

Procedure manual for the estimation of average indoor radon-daughter concentrations using the radon grab-sampling method

International Nuclear Information System (INIS)

George, J.L.

1986-04-01

The US Department of Energy (DOE) Office of Remedial Action and Waste Technology established the Technical Measurements Center to provide standardization, calibration, comparability, verification of data, quality assurance, and cost-effectiveness for the measurement requirements of DOE remedial action programs. One of the remedial-action measurement needs is the estimation of average indoor radon-daughter concentration. One method for accomplishing such estimations in support of DOE remedial action programs is the radon grab-sampling method. This manual describes procedures for radon grab sampling, with the application specifically directed to the estimation of average indoor radon-daughter concentration (RDC) in highly ventilated structures. This particular application of the measurement method is for cases where RDC estimates derived from long-term integrated measurements under occupied conditions are below the standard and where the structure being evaluated is considered to be highly ventilated. The radon grab-sampling method requires that sampling be conducted under standard maximized conditions. Briefly, the procedure for radon grab sampling involves the following steps: selection of sampling and counting equipment; sample acquisition and processing, including data reduction; calibration of equipment, including provisions to correct for pressure effects when sampling at various elevations; and incorporation of quality-control and assurance measures. This manual describes each of the above steps in detail and presents an example of a step-by-step radon grab-sampling procedure using a scintillation cell

Estimates of Inequality Indices Based on Simple Random, Ranked Set, and Systematic Sampling

OpenAIRE

Bansal, Pooja; Arora, Sangeeta; Mahajan, Kalpana K.

2013-01-01

Gini index, Bonferroni index, and Absolute Lorenz index are some popular indices of inequality showing different features of inequality measurement. In general simple random sampling procedure is commonly used to estimate the inequality indices and their related inference. The key condition that the samples must be drawn via simple random sampling procedure though makes calculations much simpler but this assumption is often violated in practice as the data does not always yield simple random ...

Time delay estimation in a reverberant environment by low rate sampling of impulsive acoustic sources

KAUST Repository

Omer, Muhammad

2012-07-01

This paper presents a new method of time delay estimation (TDE) using low sample rates of an impulsive acoustic source in a room environment. The proposed method finds the time delay from the room impulse response (RIR) which makes it robust against room reverberations. The RIR is considered a sparse phenomenon and a recently proposed sparse signal reconstruction technique called orthogonal clustering (OC) is utilized for its estimation from the low rate sampled received signal. The arrival time of the direct path signal at a pair of microphones is identified from the estimated RIR and their difference yields the desired time delay. Low sampling rates reduce the hardware and computational complexity and decrease the communication between the microphones and the centralized location. The performance of the proposed technique is demonstrated by numerical simulations and experimental results. © 2012 IEEE.

Clinical usefulness of limited sampling strategies for estimating AUC of proton pump inhibitors.

Science.gov (United States)

Niioka, Takenori

2011-03-01

Cytochrome P450 (CYP) 2C19 (CYP2C19) genotype is regarded as a useful tool to predict area under the blood concentration-time curve (AUC) of proton pump inhibitors (PPIs). In our results, however, CYP2C19 genotypes had no influence on AUC of all PPIs during fluvoxamine treatment. These findings suggest that CYP2C19 genotyping is not always a good indicator for estimating AUC of PPIs. Limited sampling strategies (LSS) were developed to estimate AUC simply and accurately. It is important to minimize the number of blood samples because of patient's acceptance. This article reviewed the usefulness of LSS for estimating AUC of three PPIs (omeprazole: OPZ, lansoprazole: LPZ and rabeprazole: RPZ). The best prediction formulas in each PPI were AUC(OPZ)=9.24 x C(6h)+2638.03, AUC(LPZ)=12.32 x C(6h)+3276.09 and AUC(RPZ)=1.39 x C(3h)+7.17 x C(6h)+344.14, respectively. In order to optimize the sampling strategy of LPZ, we tried to establish LSS for LPZ using a time point within 3 hours through the property of pharmacokinetics of its enantiomers. The best prediction formula using the fewest sampling points (one point) was AUC(racemic LPZ)=6.5 x C(3h) of (R)-LPZ+13.7 x C(3h) of (S)-LPZ-9917.3 x G1-14387.2×G2+7103.6 (G1: homozygous extensive metabolizer is 1 and the other genotypes are 0; G2: heterozygous extensive metabolizer is 1 and the other genotypes are 0). Those strategies, plasma concentration monitoring at one or two time-points, might be more suitable for AUC estimation than reference to CYP2C19 genotypes, particularly in the case of coadministration of CYP mediators.

A model for estimating the minimum number of offspring to sample in studies of reproductive success.

Science.gov (United States)

Anderson, Joseph H; Ward, Eric J; Carlson, Stephanie M

2011-01-01

Molecular parentage permits studies of selection and evolution in fecund species with cryptic mating systems, such as fish, amphibians, and insects. However, there exists no method for estimating the number of offspring that must be assigned parentage to achieve robust estimates of reproductive success when only a fraction of offspring can be sampled. We constructed a 2-stage model that first estimated the mean (μ) and variance (v) in reproductive success from published studies on salmonid fishes and then sampled offspring from reproductive success distributions simulated from the μ and v estimates. Results provided strong support for modeling salmonid reproductive success via the negative binomial distribution and suggested that few offspring samples are needed to reject the null hypothesis of uniform offspring production. However, the sampled reproductive success distributions deviated significantly (χ(2) goodness-of-fit test p value reproductive success distribution at rates often >0.05 and as high as 0.24, even when hundreds of offspring were assigned parentage. In general, reproductive success patterns were less accurate when offspring were sampled from cohorts with larger numbers of parents and greater variance in reproductive success. Our model can be reparameterized with data from other species and will aid researchers in planning reproductive success studies by providing explicit sampling targets required to accurately assess reproductive success.

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

Science.gov (United States)

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

An Empirical Study of Parameter Estimation for Stated Preference Experimental Design

Directory of Open Access Journals (Sweden)

Fei Yang

2014-01-01

Full Text Available The stated preference experimental design can affect the reliability of the parameters estimation in discrete choice model. Some scholars have proposed some new experimental designs, such as D-efficient, Bayesian D-efficient. But insufficient empirical research has been conducted on the effectiveness of these new designs and there has been little comparative analysis of the new designs against the traditional designs. In this paper, a new metro connecting Chengdu and its satellite cities is taken as the research subject to demonstrate the validity of the D-efficient and Bayesian D-efficient design. Comparisons between these new designs and orthogonal design were made by the fit of model and standard deviation of parameters estimation; then the best model result is obtained to analyze the travel choice behavior. The results indicate that Bayesian D-efficient design works better than D-efficient design. Some of the variables can affect significantly the choice behavior of people, including the waiting time and arrival time. The D-efficient and Bayesian D-efficient design for MNL can acquire reliability result in ML model, but the ML model cannot develop the theory advantages of these two designs. Finally, the metro can handle over 40% passengers flow if the metro will be operated in the future.

Non-parametric adaptive importance sampling for the probability estimation of a launcher impact position

International Nuclear Information System (INIS)

Morio, Jerome

2011-01-01

Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.

Fast Estimation of Expected Information Gain for Bayesian Experimental Design Based on Laplace Approximation

KAUST Repository

Long, Quan; Scavino, Marco; Tempone, Raul; Wang, Suojin

2014-01-01

Shannon-type expected information gain is an important utility in evaluating the usefulness of a proposed experiment that involves uncertainty. Its estimation, however, cannot rely solely on Monte Carlo sampling methods, that are generally too computationally expensive for realistic physical models, especially for those involving the solution of stochastic partial differential equations. In this work we present a new methodology, based on the Laplace approximation of the posterior probability density function, to accelerate the estimation of expected information gain in the model parameters and predictive quantities of interest. Furthermore, in order to deal with the issue of dimensionality in a complex problem, we use sparse quadratures for the integration over the prior. We show the accuracy and efficiency of the proposed method via several nonlinear numerical examples, including a single parameter design of one dimensional cubic polynomial function and the current pattern for impedance tomography.

Fast Estimation of Expected Information Gain for Bayesian Experimental Design Based on Laplace Approximation

KAUST Repository

Long, Quan

2014-01-06

Shannon-type expected information gain is an important utility in evaluating the usefulness of a proposed experiment that involves uncertainty. Its estimation, however, cannot rely solely on Monte Carlo sampling methods, that are generally too computationally expensive for realistic physical models, especially for those involving the solution of stochastic partial differential equations. In this work we present a new methodology, based on the Laplace approximation of the posterior probability density function, to accelerate the estimation of expected information gain in the model parameters and predictive quantities of interest. Furthermore, in order to deal with the issue of dimensionality in a complex problem, we use sparse quadratures for the integration over the prior. We show the accuracy and efficiency of the proposed method via several nonlinear numerical examples, including a single parameter design of one dimensional cubic polynomial function and the current pattern for impedance tomography.

Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

International Nuclear Information System (INIS)

Wattanapongskorn, Naruemon; Coit, David W.

2007-01-01

In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed

Importance of sampling design and analysis in animal population studies: a comment on Sergio et al

Science.gov (United States)

Kery, M.; Royle, J. Andrew; Schmid, Hans

2008-01-01

1. The use of predators as indicators and umbrellas in conservation has been criticized. In the Trentino region, Sergio et al. (2006; hereafter SEA) counted almost twice as many bird species in quadrats located in raptor territories than in controls. However, SEA detected astonishingly few species. We used contemporary Swiss Breeding Bird Survey data from an adjacent region and a novel statistical model that corrects for overlooked species to estimate the expected number of bird species per quadrat in that region. 2. There are two anomalies in SEA which render their results ambiguous. First, SEA detected on average only 6.8 species, whereas a value of 32 might be expected. Hence, they probably overlooked almost 80% of all species. Secondly, the precision of their mean species counts was greater in two-thirds of cases than in the unlikely case that all quadrats harboured exactly the same number of equally detectable species. This suggests that they detected consistently only a biased, unrepresentative subset of species. 3. Conceptually, expected species counts are the product of true species number and species detectability p. Plenty of factors may affect p, including date, hour, observer, previous knowledge of a site and mobbing behaviour of passerines in the presence of predators. Such differences in p between raptor and control quadrats could have easily created the observed effects. Without a method that corrects for such biases, or without quantitative evidence that species detectability was indeed similar between raptor and control quadrats, the meaning of SEA's counts is hard to evaluate. Therefore, the evidence presented by SEA in favour of raptors as indicator species for enhanced levels of biodiversity remains inconclusive. 4. Synthesis and application. Ecologists should pay greater attention to sampling design and analysis in animal population estimation. Species richness estimation means sampling a community. Samples should be representative for the

The Impact of Statistical Leakage Models on Design Yield Estimation

Directory of Open Access Journals (Sweden)

Rouwaida Kanj

2011-01-01

Full Text Available Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100 nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.

Point and Fixed Plot Sampling Inventory Estimates at the Savannah River Site, South Carolina.

Energy Technology Data Exchange (ETDEWEB)

Parresol, Bernard, R.

2004-02-01

This report provides calculation of systematic point sampling volume estimates for trees greater than or equal to 5 inches diameter breast height (dbh) and fixed radius plot volume estimates for trees < 5 inches dbh at the Savannah River Site (SRS), Aiken County, South Carolina. The inventory of 622 plots was started in March 1999 and completed in January 2002 (Figure 1). Estimates are given in cubic foot volume. The analyses are presented in a series of Tables and Figures. In addition, a preliminary analysis of fuel levels on the SRS is given, based on depth measurements of the duff and litter layers on the 622 inventory plots plus line transect samples of down coarse woody material. Potential standing live fuels are also included. The fuels analyses are presented in a series of tables.

Estimating the biological value of soft-bottom sediments with sediment profile imaging and grab sampling

Science.gov (United States)

Van Hoey, Gert; Birchenough, Silvana N. R.; Hostens, Kris

2014-02-01

Biological value estimation is based on a set of assessment questions and several thresholds to delineate areas of ecological importance (e.g. biodiversity). An existing framework, that was specifically designed to assess the ecosystem biodiversity, was expanded by adding new questions on the productivity, functionality and biogeochemical status of benthic habitats. The additional ecological and sedimentological information was collected by using sediment profile imagery (SPI) and grab sampling. Additionally, information on the performance and comparability of both techniques is provided in this study. The research idea was tested at a site near the harbor of Zeebrugge, an area under consideration as a new disposal site for dredged material from the harbor entrance. The sedimentology of the area can be adequately described based on the information from both SPI and Van Veen grab samples, but only the SPI revealed structural information on the physical habitat (layering, a-RPD). The latter information represented the current status of the benthic habitat, which was confirmed by the Van Veen grab samples. All information was summarized through the biological valuation framework, and provided clear evidence of the differences in biological value for the different sediment types within the area. We concluded that the installation of a new dredged material disposal site in this area was not in conflict with the benthic ecology. This area has a low biological value and the benthic system is adapted to changing conditions, which was signaled by the dominance of mobile, short living and opportunistic species. This study showed that suitable sedimentological and ecological information can be gathered by these traditional and complementary techniques, to estimate the biological value of an area in the light of marine spatial planning and environmental impact assessments.

Estimating cross-validatory predictive p-values with integrated importance sampling for disease mapping models.

Science.gov (United States)

Li, Longhai; Feng, Cindy X; Qiu, Shi

2017-06-30

An important statistical task in disease mapping problems is to identify divergent regions with unusually high or low risk of disease. Leave-one-out cross-validatory (LOOCV) model assessment is the gold standard for estimating predictive p-values that can flag such divergent regions. However, actual LOOCV is time-consuming because one needs to rerun a Markov chain Monte Carlo analysis for each posterior distribution in which an observation is held out as a test case. This paper introduces a new method, called integrated importance sampling (iIS), for estimating LOOCV predictive p-values with only Markov chain samples drawn from the posterior based on a full data set. The key step in iIS is that we integrate away the latent variables associated the test observation with respect to their conditional distribution without reference to the actual observation. By following the general theory for importance sampling, the formula used by iIS can be proved to be equivalent to the LOOCV predictive p-value. We compare iIS and other three existing methods in the literature with two disease mapping datasets. Our empirical results show that the predictive p-values estimated with iIS are almost identical to the predictive p-values estimated with actual LOOCV and outperform those given by the existing three methods, namely, the posterior predictive checking, the ordinary importance sampling, and the ghosting method by Marshall and Spiegelhalter (2003). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Considerations in Forest Growth Estimation Between Two Measurements of Mapped Forest Inventory Plots

Science.gov (United States)

Michael T. Thompson

2006-01-01

Several aspects of the enhanced Forest Inventory and Analysis (FIA) program?s national plot design complicate change estimation. The design incorporates up to three separate plot sizes (microplot, subplot, and macroplot) to sample trees of different sizes. Because multiple plot sizes are involved, change estimators designed for polyareal plot sampling, such as those...

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

Science.gov (United States)

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

Science.gov (United States)

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

Science.gov (United States)

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Investigation of Bicycle Travel Time Estimation Using Bluetooth Sensors for Low Sampling Rates

Directory of Open Access Journals (Sweden)

Zhenyu Mei

2014-10-01

Full Text Available Filtering the data for bicycle travel time using Bluetooth sensors is crucial to the estimation of link travel times on a corridor. The current paper describes an adaptive filtering algorithm for estimating bicycle travel times using Bluetooth data, with consideration of low sampling rates. The data for bicycle travel time using Bluetooth sensors has two characteristics. First, the bicycle flow contains stable and unstable conditions. Second, the collected data have low sampling rates (less than 1%. To avoid erroneous inference, filters are introduced to “purify” multiple time series. The valid data are identified within a dynamically varying validity window with the use of a robust data-filtering procedure. The size of the validity window varies based on the number of preceding sampling intervals without a Bluetooth record. Applications of the proposed algorithm to the dataset from Genshan East Road and Moganshan Road in Hangzhou demonstrate its ability to track typical variations in bicycle travel time efficiently, while suppressing high frequency noise signals.

Variable selection and estimation for longitudinal survey data

KAUST Repository

Wang, Li

2014-09-01

There is wide interest in studying longitudinal surveys where sample subjects are observed successively over time. Longitudinal surveys have been used in many areas today, for example, in the health and social sciences, to explore relationships or to identify significant variables in regression settings. This paper develops a general strategy for the model selection problem in longitudinal sample surveys. A survey weighted penalized estimating equation approach is proposed to select significant variables and estimate the coefficients simultaneously. The proposed estimators are design consistent and perform as well as the oracle procedure when the correct submodel was known. The estimating function bootstrap is applied to obtain the standard errors of the estimated parameters with good accuracy. A fast and efficient variable selection algorithm is developed to identify significant variables for complex longitudinal survey data. Simulated examples are illustrated to show the usefulness of the proposed methodology under various model settings and sampling designs. © 2014 Elsevier Inc.

Design development of robotic system for on line sampling in fuel reprocessing

International Nuclear Information System (INIS)

Balasubramanian, G.R.; Venugopal, P.R.; Padmashali, G.K.

1990-01-01

This presentation describes the design and developmental work that is being carried out for the design of an automated sampling system for fast reactor fuel reprocessing plants. The plant proposes to use integrated sampling system. The sample is taken across regular process streams from any intermediate hold up pot. A robot system is planned to take the sample from the sample pot, transfer it to the sample bottle, cap the bottle and transfer the bottle to a pneumatic conveying station. The system covers a large number of sample pots. Alternate automated systems are also examined (1). (author). 4 refs., 2 figs

How many dinosaur species were there? Fossil bias and true richness estimated using a Poisson sampling model.

Science.gov (United States)

Starrfelt, Jostein; Liow, Lee Hsiang

2016-04-05

The fossil record is a rich source of information about biological diversity in the past. However, the fossil record is not only incomplete but has also inherent biases due to geological, physical, chemical and biological factors. Our knowledge of past life is also biased because of differences in academic and amateur interests and sampling efforts. As a result, not all individuals or species that lived in the past are equally likely to be discovered at any point in time or space. To reconstruct temporal dynamics of diversity using the fossil record, biased sampling must be explicitly taken into account. Here, we introduce an approach that uses the variation in the number of times each species is observed in the fossil record to estimate both sampling bias and true richness. We term our technique TRiPS (True Richness estimated using a Poisson Sampling model) and explore its robustness to violation of its assumptions via simulations. We then venture to estimate sampling bias and absolute species richness of dinosaurs in the geological stages of the Mesozoic. Using TRiPS, we estimate that 1936 (1543-2468) species of dinosaurs roamed the Earth during the Mesozoic. We also present improved estimates of species richness trajectories of the three major dinosaur clades: the sauropodomorphs, ornithischians and theropods, casting doubt on the Jurassic-Cretaceous extinction event and demonstrating that all dinosaur groups are subject to considerable sampling bias throughout the Mesozoic. © 2016 The Authors.

Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes

Directory of Open Access Journals (Sweden)

Heinz Gallaun

2015-09-01

Full Text Available Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.

Estimation of technetium 99m mercaptoacetyltriglycine plasma clearance by use of one single plasma sample

International Nuclear Information System (INIS)

Mueller-Suur, R.; Magnusson, G.; Karolinska Inst., Stockholm; Bois-Svensson, I.; Jansson, B.

1991-01-01

Recent studies have shown that technetium 99m mercaptoacetyltriglycine (MAG-3) is a suitable replacement for iodine 131 or 123 hippurate in gamma-camera renography. Also, the determination of its clearance is of value, since it correlates well with that of hippurate and thus may be an indirect measure of renal plasma flow. In order to simplify the clearance method we developed formulas for the estimation of plasma clearance of MAG-3 based on a single plasma sample and compared them with the multiple sample method based on 7 plasma samples. The correlation to effective renal plasma flow (ERPF) (according to Tauxe's method, using iodine 123 hippurate), which ranged from 75 to 654 ml/min per 1.73 m 2 , was determined in these patients. Using the developed regression equations the error of estimate for the simplified clearance method was acceptably low (18-14 ml/min), when the single plasma sample was taken 44-64 min post-injection. Formulas for different sampling times at 44, 48, 52, 56, 60 and 64 min are given, and we recommend 60 min as optimal, with an error of estimate of 15.5 ml/min. The correlation between the MAG-3 clearances and ERPF was high (r=0.90). Since normal values for MAG-3 clearance are not yet available, transformation to estimated ERPF values by the regression equation (ERPF=1.86xC MAG-3 +4.6) could be of clinical value in order to compare it with the normal values for ERPF given in the literature. (orig.)

Intra-class correlation estimates for assessment of vitamin A intake in children.

Science.gov (United States)

Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

2005-03-01

In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

Uncertainties in early-stage capital cost estimation of process design – a case study on biorefinery design

DEFF Research Database (Denmark)

Cheali, Peam; Gernaey, Krist; Sin, Gürkan

2015-01-01

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which......) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design...

Stratified sampling design based on data mining.

Science.gov (United States)

Kim, Yeonkook J; Oh, Yoonhwan; Park, Sunghoon; Cho, Sungzoon; Park, Hayoung

2013-09-01

To explore classification rules based on data mining methodologies which are to be used in defining strata in stratified sampling of healthcare providers with improved sampling efficiency. We performed k-means clustering to group providers with similar characteristics, then, constructed decision trees on cluster labels to generate stratification rules. We assessed the variance explained by the stratification proposed in this study and by conventional stratification to evaluate the performance of the sampling design. We constructed a study database from health insurance claims data and providers' profile data made available to this study by the Health Insurance Review and Assessment Service of South Korea, and population data from Statistics Korea. From our database, we used the data for single specialty clinics or hospitals in two specialties, general surgery and ophthalmology, for the year 2011 in this study. Data mining resulted in five strata in general surgery with two stratification variables, the number of inpatients per specialist and population density of provider location, and five strata in ophthalmology with two stratification variables, the number of inpatients per specialist and number of beds. The percentages of variance in annual changes in the productivity of specialists explained by the stratification in general surgery and ophthalmology were 22% and 8%, respectively, whereas conventional stratification by the type of provider location and number of beds explained 2% and 0.2% of variance, respectively. This study demonstrated that data mining methods can be used in designing efficient stratified sampling with variables readily available to the insurer and government; it offers an alternative to the existing stratification method that is widely used in healthcare provider surveys in South Korea.

Differences in Movement Pattern and Detectability between Males and Females Influence How Common Sampling Methods Estimate Sex Ratio.

Directory of Open Access Journals (Sweden)

João Fabrício Mota Rodrigues

Full Text Available Sampling the biodiversity is an essential step for conservation, and understanding the efficiency of sampling methods allows us to estimate the quality of our biodiversity data. Sex ratio is an important population characteristic, but until now, no study has evaluated how efficient are the sampling methods commonly used in biodiversity surveys in estimating the sex ratio of populations. We used a virtual ecologist approach to investigate whether active and passive capture methods are able to accurately sample a population's sex ratio and whether differences in movement pattern and detectability between males and females produce biased estimates of sex-ratios when using these methods. Our simulation allowed the recognition of individuals, similar to mark-recapture studies. We found that differences in both movement patterns and detectability between males and females produce biased estimates of sex ratios. However, increasing the sampling effort or the number of sampling days improves the ability of passive or active capture methods to properly sample sex ratio. Thus, prior knowledge regarding movement patterns and detectability for species is important information to guide field studies aiming to understand sex ratio related patterns.

Differences in Movement Pattern and Detectability between Males and Females Influence How Common Sampling Methods Estimate Sex Ratio.

Science.gov (United States)

Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco

2016-01-01

Sampling the biodiversity is an essential step for conservation, and understanding the efficiency of sampling methods allows us to estimate the quality of our biodiversity data. Sex ratio is an important population characteristic, but until now, no study has evaluated how efficient are the sampling methods commonly used in biodiversity surveys in estimating the sex ratio of populations. We used a virtual ecologist approach to investigate whether active and passive capture methods are able to accurately sample a population's sex ratio and whether differences in movement pattern and detectability between males and females produce biased estimates of sex-ratios when using these methods. Our simulation allowed the recognition of individuals, similar to mark-recapture studies. We found that differences in both movement patterns and detectability between males and females produce biased estimates of sex ratios. However, increasing the sampling effort or the number of sampling days improves the ability of passive or active capture methods to properly sample sex ratio. Thus, prior knowledge regarding movement patterns and detectability for species is important information to guide field studies aiming to understand sex ratio related patterns.

Latent spatial models and sampling design for landscape genetics

Science.gov (United States)

Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

Uncertainties in Early Stage Capital Cost Estimation of Process Design – A case study on biorefinery design

Directory of Open Access Journals (Sweden)

Gurkan eSin

2015-02-01

Full Text Available Capital investment, next to the product demand, sales and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early stage design is a challenging task. This is especially important in biorefinery research, where available information and experiences with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs (a Bootstrapping as a regression method when cost data is available and (b the Monte Carlo technique as an error propagation method based on expert input when cost data is not available. Four well-known models for early stage cost estimation are reviewed an analyzed using the methodology. The significance of uncertainties of cost data for early stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision making under uncertainties. One of the results using an order-of-magnitude estimate shows that the production of diethyl ether and 1,3-butadiene are the most promising with economic risks of 0.24 MM$/a and 4.6 MM$/a due to uncertainties in cost estimations, respectively.

Variance estimation for generalized Cavalieri estimators

OpenAIRE

Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

2011-01-01

The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

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

Visual Sample Plan (VSP) Software: Designs and Data Analyses for Sampling Contaminated Buildings

International Nuclear Information System (INIS)

Pulsipher, Brent A.; Wilson, John E.; Gilbert, Richard O.; Nuffer, Lisa L.; Hassig, Nancy L.

2005-01-01

A new module of the Visual Sample Plan (VSP) software has been developed to provide sampling designs and data analyses for potentially contaminated buildings. An important application is assessing levels of contamination in buildings after a terrorist attack. This new module, funded by DHS through the Combating Terrorism Technology Support Office, Technical Support Working Group, was developed to provide a tailored, user-friendly and visually-orientated buildings module within the existing VSP software toolkit, the latest version of which can be downloaded from http://dqo.pnl.gov/vsp. In case of, or when planning against, a chemical, biological, or radionuclide release within a building, the VSP module can be used to quickly and easily develop and visualize technically defensible sampling schemes for walls, floors, ceilings, and other surfaces to statistically determine if contamination is present, its magnitude and extent throughout the building and if decontamination has been effective. This paper demonstrates the features of this new VSP buildings module, which include: the ability to import building floor plans or to easily draw, manipulate, and view rooms in several ways; being able to insert doors, windows and annotations into a room; 3-D graphic room views with surfaces labeled and floor plans that show building zones that have separate air handing units. The paper will also discuss the statistical design and data analysis options available in the buildings module. Design objectives supported include comparing an average to a threshold when the data distribution is normal or unknown, and comparing measurements to a threshold to detect hotspots or to insure most of the area is uncontaminated when the data distribution is normal or unknown

Uncertainty Estimation of Neutron Activation Analysis in Zinc Elemental Determination in Food Samples

International Nuclear Information System (INIS)

Endah Damastuti; Muhayatun; Diah Dwiana L

2009-01-01

Beside to complished the requirements of international standard of ISO/IEC 17025:2005, uncertainty estimation should be done to increase quality and confidence of analysis results and also to establish traceability of the analysis results to SI unit. Neutron activation analysis is a major technique used by Radiometry technique analysis laboratory and is included as scope of accreditation under ISO/IEC 17025:2005, therefore uncertainty estimation of neutron activation analysis is needed to be carried out. Sample and standard preparation as well as, irradiation and measurement using gamma spectrometry were the main activities which could give contribution to uncertainty. The components of uncertainty sources were specifically explained. The result of expanded uncertainty was 4,0 mg/kg with level of confidence 95% (coverage factor=2) and Zn concentration was 25,1 mg/kg. Counting statistic of cuplikan and standard were the major contribution of combined uncertainty. The uncertainty estimation was expected to increase the quality of the analysis results and could be applied further to other kind of samples. (author)

Low Power Design with High-Level Power Estimation and Power-Aware Synthesis

CERN Document Server

Ahuja, Sumit; Shukla, Sandeep Kumar

2012-01-01

Low-power ASIC/FPGA based designs are important due to the need for extended battery life, reduced form factor, and lower packaging and cooling costs for electronic devices. These products require fast turnaround time because of the increasing demand for handheld electronic devices such as cell-phones, PDAs and high performance machines for data centers. To achieve short time to market, design flows must facilitate a much shortened time-to-product requirement. High-level modeling, architectural exploration and direct synthesis of design from high level description enable this design process. This book presents novel research techniques, algorithms,methodologies and experimental results for high level power estimation and power aware high-level synthesis. Readers will learn to apply such techniques to enable design flows resulting in shorter time to market and successful low power ASIC/FPGA design. Integrates power estimation and reduction for high level synthesis, with low-power, high-level design; Shows spec...

Some remarks on estimating a covariance structure model from a sample correlation matrix

OpenAIRE

Maydeu Olivares, Alberto; Hernández Estrada, Adolfo

2000-01-01

A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...

Fast estimation of expected information gains for Bayesian experimental designs based on Laplace approximations

KAUST Repository

Long, Quan; Scavino, Marco; Tempone, Raul; Wang, Suojin

2013-01-01

Shannon-type expected information gain can be used to evaluate the relevance of a proposed experiment subjected to uncertainty. The estimation of such gain, however, relies on a double-loop integration. Moreover, its numerical integration in multi-dimensional cases, e.g., when using Monte Carlo sampling methods, is therefore computationally too expensive for realistic physical models, especially for those involving the solution of partial differential equations. In this work, we present a new methodology, based on the Laplace approximation for the integration of the posterior probability density function (pdf), to accelerate the estimation of the expected information gains in the model parameters and predictive quantities of interest. We obtain a closed-form approximation of the inner integral and the corresponding dominant error term in the cases where parameters are determined by the experiment, such that only a single-loop integration is needed to carry out the estimation of the expected information gain. To deal with the issue of dimensionality in a complex problem, we use a sparse quadrature for the integration over the prior pdf. We demonstrate the accuracy, efficiency and robustness of the proposed method via several nonlinear numerical examples, including the designs of the scalar parameter in a one-dimensional cubic polynomial function, the design of the same scalar in a modified function with two indistinguishable parameters, the resolution width and measurement time for a blurred single peak spectrum, and the boundary source locations for impedance tomography in a square domain. © 2013 Elsevier B.V.

Fast estimation of expected information gains for Bayesian experimental designs based on Laplace approximations

KAUST Repository

Long, Quan

2013-06-01

Shannon-type expected information gain can be used to evaluate the relevance of a proposed experiment subjected to uncertainty. The estimation of such gain, however, relies on a double-loop integration. Moreover, its numerical integration in multi-dimensional cases, e.g., when using Monte Carlo sampling methods, is therefore computationally too expensive for realistic physical models, especially for those involving the solution of partial differential equations. In this work, we present a new methodology, based on the Laplace approximation for the integration of the posterior probability density function (pdf), to accelerate the estimation of the expected information gains in the model parameters and predictive quantities of interest. We obtain a closed-form approximation of the inner integral and the corresponding dominant error term in the cases where parameters are determined by the experiment, such that only a single-loop integration is needed to carry out the estimation of the expected information gain. To deal with the issue of dimensionality in a complex problem, we use a sparse quadrature for the integration over the prior pdf. We demonstrate the accuracy, efficiency and robustness of the proposed method via several nonlinear numerical examples, including the designs of the scalar parameter in a one-dimensional cubic polynomial function, the design of the same scalar in a modified function with two indistinguishable parameters, the resolution width and measurement time for a blurred single peak spectrum, and the boundary source locations for impedance tomography in a square domain. © 2013 Elsevier B.V.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

Science.gov (United States)

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

Correcting for Systematic Bias in Sample Estimates of Population Variances: Why Do We Divide by n-1?

Science.gov (United States)

Mittag, Kathleen Cage

An important topic presented in introductory statistics courses is the estimation of population parameters using samples. Students learn that when estimating population variances using sample data, we always get an underestimate of the population variance if we divide by n rather than n-1. One implication of this correction is that the degree of…

Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion)

NARCIS (Netherlands)

Brus, D.J.; Gruijter, de J.J.

1997-01-01

Classical sampling theory has been repeatedly identified with classical statistics which assumes that data are identically and independently distributed. This explains the switch of many soil scientists from design-based sampling strategies, based on classical sampling theory, to the model-based