Lanterna Rally
eBook PDF Download Digital Library
Finite Population Sampling and Inference
Author: Richard Valliant
Publisher: Wiley-Interscience
Published: 2000-09-08
Total Pages: 546
ISBN-13:
DOWNLOAD EBOOK →Complete coverage of the prediction approach to survey sampling in a single resource Prediction theory has been extremely influential in survey sampling for nearly three decades, yet research findings on this model-based approach are scattered in disparate areas of the statistical literature. Finite Population Sampling and Inference: A Prediction Approach presents for the first time a unified treatment of sample design and estimation for finite populations from a prediction point of view, providing readers with access to a wealth of theoretical results, including many new results and, a variety of practical applications. Geared to theoretical statisticians and practitioners alike, the book discusses all topics from the ground up and clearly explains the relation of the prediction approach to the traditional design-based randomization approach. Key features include: * Special emphasis on linking survey sampling to mainstream statistics through extensive use of general linear models * A liberal use of simulation studies, numerical examples, and exercises illustrating theoretical results * Numerous statistical graphics showing simulation results and properties of estimates * A library of S-Plus computer functions plus six real populations, available via ftp * Over 260 references to finite population sampling, linear models, and other relevant literature
Bayesian Methods for Finite Population Sampling
Author: Malay Ghosh
Publisher: CRC Press
Published: 1997-06-01
Total Pages: 304
ISBN-13: 9780412987717
DOWNLOAD EBOOK →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.
Foundations of Inference in Survey Sampling
Author: Claes-Magnus Cassel
Publisher:
Published: 1977-08-31
Total Pages: 216
ISBN-13:
DOWNLOAD EBOOK →Basic model of sampling from a population with identifiable units; Inference under the fixed population model: the concepts of sufficiency and likelihood; inference under the fixed population model: criteria for judging estimators and strategies; Inference under superpopulation models: design-unbiased estimation; Inference under superpopulation models: prediction approach using tools of classical inference; Inference under superpopulation models: using tools of bayesian inference; Efficiency robust estimation of the finite population mean.
Studies in Statistical Inference, Sample Techniques and Demography
Author: Rajesh Singh, Jayant Singh, Florentin Smarandache
Publisher: Infinite Study
Published: 2009
Total Pages: 64
ISBN-13: 1599730871
DOWNLOAD EBOOK →This volume is a collection of five papers/chapters. Two chapters deal withproblems in statistical inference, two with inferences in finite population, and one deals with demographic problem. The ideas included here will be useful for researchers doing works in these fields.
Sampling Strategies for Finite Population Using Auxiliary Information
Author: Rajesh Singh, Florentin Smarandache
Publisher: Infinite Study
Published: 2015-05-15
Total Pages: 56
ISBN-13: 159973348X
DOWNLOAD EBOOK →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.
Bayesian Methods for Finite Population Sampling
Author: Malay Ghosh
Publisher: Routledge
Published: 2021-12-17
Total Pages: 296
ISBN-13: 1351464426
DOWNLOAD EBOOK →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.
Design and Inference in Finite Population Sampling
Author: A. S. Hedayat
Publisher: Wiley-Interscience
Published: 1991-09-03
Total Pages: 0
ISBN-13: 9780471880738
DOWNLOAD EBOOK →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.
Ranked Set Sampling
Author: Carlos N. Bouza-Herrera
Publisher: Academic Press
Published: 2018-10-16
Total Pages: 314
ISBN-13: 0128156937
DOWNLOAD EBOOK →Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs. Focuses on how researchers should manipulate RSS techniques for specific applications Discusses RSS performs in popular statistical models, such as regression and hypothesis testing Includes a discussion of open theoretical research problems Provides mathematical proofs, enabling researchers to develop new models
Sampling and Estimation from Finite Populations
Author: Yves Tille
Publisher: John Wiley & Sons
Published: 2020-03-30
Total Pages: 447
ISBN-13: 0470682051
DOWNLOAD EBOOK →A much-needed reference on survey sampling and its applications that presents the latest advances in the field Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foundations of survey sampling. It offers readers a critical approach to the subject and discusses putting theory into practice. It also explores the treatment of non-sampling errors featuring a range of topics from the problems of coverage to the treatment of non-response. In addition, the book includes real examples, applications, and a large set of exercises with solutions. Sampling and Estimation from Finite Populations begins with a look at the history of survey sampling. It then offers chapters on: population, sample, and estimation; simple and systematic designs; stratification; sampling with unequal probabilities; balanced sampling; cluster and two-stage sampling; and other topics on sampling, such as spatial sampling, coordination in repeated surveys, and multiple survey frames. The book also includes sections on: post-stratification and calibration on marginal totals; calibration estimation; estimation of complex parameters; variance estimation by linearization; and much more. Provides an up-to-date review of the theory of sampling Discusses the foundation of inference in survey sampling, in particular, the model-based and design-based frameworks Reviews the problems of application of the theory into practice Also deals with the treatment of non sampling errors Sampling and Estimation from Finite Populations is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.
