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Bayesian Methods for Finite Population Sampling

Bayesian Methods for Finite Population Sampling
Author: Malay Ghosh
Publisher: Routledge
Total Pages: 296
Release: 2021-12-17
Genre: Mathematics
ISBN: 1351464426

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Assuming a basic knowledge of the frequentist approach to finite population sampling, Bayesian Methods for Finite Population Sampling describes Bayesian and predictive approaches to inferential problems with an emphasis on the likelihood principle. The authors demonstrate that a variety of levels of prior information can be used in survey sampling in a Bayesian manner. Situations considered range from a noninformative Bayesian justification of standard frequentist methods when the only prior information available is the belief in the exchangeability of the units to a full-fledged Bayesian model. Intended primarily for graduate students and researchers in finite population sampling, this book will also be of interest to statisticians who use sampling and lecturers and researchers in general statistics and biostatistics.


Sampling from a Finite Population

Sampling from a Finite Population
Author: Jaroslav Hájek
Publisher:
Total Pages: 270
Release: 1981
Genre: Mathematics
ISBN:

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Basic ideas and concepts; Methods of sampling; Methods of estimation.


Design and Inference in Finite Population Sampling

Design and Inference in Finite Population Sampling
Author: A. S. Hedayat
Publisher: Wiley-Interscience
Total Pages: 0
Release: 1991-09-03
Genre: Science
ISBN: 9780471880738

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Covers a new but essential development in the field of population sampling, namely inference in finite sampling. Offers some important topics not found in other texts on sampling such as the superpopulation approach and randomized response, nonresponse and resampling techniques.


A Note on Sampling to Locate Rare Defectives with Strong Prior Evidence

A Note on Sampling to Locate Rare Defectives with Strong Prior Evidence
Author: Tommy Wright
Publisher:
Total Pages: 7
Release: 2002
Genre: Bayesian statistical decision theory
ISBN:

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Inference about the number of defectives in a finite population is considered. Using a Bayesian model for computing the probability of unobserved defectives given the results of the sample, a criterion for sample size determination is introduced for two cases: (i) when there is a uniform prior, and (ii) when there is strong prior information. Depending on the value of the population size N, the savings in terms of a sampling effort rather than a census can be significant. When there is strong prior information, an explicit decision rule is given for determining whether a sample is needed or if the prior information alone is sufficient.


Sampling Strategies for Finite Population Using Auxiliary Information

Sampling Strategies for Finite Population Using Auxiliary Information
Author: Rajesh Singh, Florentin Smarandache
Publisher: Infinite Study
Total Pages: 56
Release: 2015-05-15
Genre: Mathematics
ISBN: 159973348X

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The present book aims to present some improved estimators using auxiliary and attribute information in case of simple random sampling and stratified random sampling and in some cases when non-response is present. This volume is a collection of five papers, written by seven co-authors (listed in the order of the papers): Sachin Malik, Rajesh Singh, Florentin Smarandache, B. B. Khare, P. S. Jha, Usha Srivastava and Habib Ur. Rehman.


Sampling of Populations

Sampling of Populations
Author: Paul S. Levy
Publisher: John Wiley & Sons
Total Pages: 213
Release: 2009-01-27
Genre: Medical
ISBN: 047040101X

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A trusted classic on the key methods in population sampling—now in a modernized and expanded new edition Sampling of Populations, Fourth Edition continues to serve as an all-inclusive resource on the basic and most current practices in population sampling. Maintaining the clear and accessible style of the previous edition, this book outlines the essential statistical methodsfor survey design and analysis, while also exploring techniques that have developed over the past decade. The Fourth Edition successfully guides the reader through the basic concepts and procedures that accompany real-world sample surveys, such as sampling designs, problems of missing data, statistical analysis of multistage sampling data, and nonresponse and poststratification adjustment procedures. Rather than employ a heavily mathematical approach, the authors present illustrative examples that demonstrate the rationale behind common steps in the sampling process, from creating effective surveys to analyzing collected data. Along with established methods, modern topics are treated through the book's new features, which include: A new chapter on telephone sampling, with coverage of declining response rates, the creation of "do not call" lists, and the growing use of cellular phones A new chapter on sample weighting that focuses on adjustments to weight for nonresponse, frame deficiencies, and the effects of estimator instability An updated discussion of sample survey data analysis that includes analytic procedures for estimation and hypothesis testing A new section on Chromy's widely used method of taking probability proportional to size samples with minimum replacement of primary sampling units An expanded index with references on the latest research in the field All of the book's examples and exercises can be easily worked out using various software packages including SAS, STATA, and SUDAAN, and an extensive FTP site contains additional data sets. With its comprehensive presentation and wealth of relevant examples, Sampling of Populations, Fourth Edition is an ideal book for courses on survey sampling at the upper-undergraduate and graduate levels. It is also a valuable reference for practicing statisticians who would like to refresh their knowledge of sampling techniques.