Small Domain Statistics
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Author | : Arijit Chaudhuri |
Publisher | : LAP Lambert Academic Publishing |
Total Pages | : 120 |
Release | : 2012-06 |
Genre | : |
ISBN | : 9783659136764 |
When a sample is taken from a population additionally for a certain of its components called domains also estimates are needed for certain parameters. When domain-wise samples are too small these estimates turn out poor in efficiency. By borrowing strength from other domains how data may be appropriately used is an important issue. How to settle this using domain as well as past data is a story related in this monograph. For this appropriate model-assisted analysis is described in details. Historical developments are narrated and live data-base emperical findings are presented in great details. Mainly the author's own research in collaboration with his students and colleagues is stressed. Contemporary research by others is also touched to the extent possible in this short output. Further a point of interest is to start with classical estimation methods based on unequal probability sampling and to follow up with appropriate modelling. This has been diligently implemented as is not usually emphasised in the current literature on Small Area Estimation.
Author | : |
Publisher | : |
Total Pages | : 10 |
Release | : 1993 |
Genre | : |
ISBN | : |
Author | : R. Platek |
Publisher | : New York ; Toronto : Wiley |
Total Pages | : 312 |
Release | : 1987-02-04 |
Genre | : Mathematics |
ISBN | : |
Presents the most recent developments in the theory and practice of small area estimation. Addresses policy issues, population estimation for small areas, theoretical developments, and organizational experiences. Discusses new techniques of estimation, including extensions of synthetic estimation techniques, Bayes and empirical Bayes methods, estimators based on regression and others.
Author | : J. N. K. Rao |
Publisher | : John Wiley & Sons |
Total Pages | : 480 |
Release | : 2015-08-24 |
Genre | : Mathematics |
ISBN | : 1118735722 |
Praise for the First Edition "This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic...I believe that it has the potential to turn small area estimation...into a larger area of importance to both researchers and practitioners." —Journal of the American Statistical Association Written by two experts in the field, Small Area Estimation, Second Edition provides a comprehensive and up-to-date account of the methods and theory of small area estimation (SAE), particularly indirect estimation based on explicit small area linking models. The model-based approach to small area estimation offers several advantages including increased precision, the derivation of "optimal" estimates and associated measures of variability under an assumed model, and the validation of models from the sample data. Emphasizing real data throughout, the Second Edition maintains a self-contained account of crucial theoretical and methodological developments in the field of SAE. The new edition provides extensive accounts of new and updated research, which often involves complex theory to handle model misspecifications and other complexities. Including information on survey design issues and traditional methods employing indirect estimates based on implicit linking models, Small Area Estimation, Second Edition also features: Additional sections describing the use of R code data sets for readers to use when replicating applications Numerous examples of SAE applications throughout each chapter, including recent applications in U.S. Federal programs New topical coverage on extended design issues, synthetic estimation, further refinements and solutions to the Fay-Herriot area level model, basic unit level models, and spatial and time series models A discussion of the advantages and limitations of various SAE methods for model selection from data as well as comparisons of estimates derived from models to reliable values obtained from external sources, such as previous census or administrative data Small Area Estimation, Second Edition is an excellent reference for practicing statisticians and survey methodologists as well as practitioners interested in learning SAE methods. The Second Edition is also an ideal textbook for graduate-level courses in SAE and reliable small area statistics.
Author | : Giorgio Alleva |
Publisher | : Springer |
Total Pages | : 306 |
Release | : 2016-05-19 |
Genre | : Mathematics |
ISBN | : 3319272748 |
This book highlights the latest research findings from the 46th International Meeting of the Italian Statistical Society (SIS) in Rome, during which both methodological and applied statistical research was discussed. This selection of fully peer-reviewed papers, originally presented at the meeting, addresses a broad range of topics, including the theory of statistical inference; data mining and multivariate statistical analysis; survey methodologies; analysis of social, demographic and health data; and economic statistics and econometrics.
Author | : American Statistical Association. Annual Meeting |
Publisher | : |
Total Pages | : 298 |
Release | : 1984 |
Genre | : Canada |
ISBN | : |
Author | : Risto Lehtonen |
Publisher | : |
Total Pages | : 111 |
Release | : 2001 |
Genre | : |
ISBN | : 9789517279888 |
Author | : Asian Development Bank |
Publisher | : Asian Development Bank |
Total Pages | : 152 |
Release | : 2020-05-01 |
Genre | : Business & Economics |
ISBN | : 9292622234 |
This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Author | : Arijit Chaudhuri |
Publisher | : PHI Learning Pvt. Ltd. |
Total Pages | : 249 |
Release | : 2010-01-30 |
Genre | : Reference |
ISBN | : 8120339703 |
How the samples are allocated to strata or to clusters? Which is the best sampling method? How large a sample size should be? Will the sample provide the precision that we require? How the best results can be obtained at the lower cost? How to design and analyze different forms of sample surveys? The author focusses on using sampling techniques and ideas to solve real problems. This text includes different sampling methods and different sample allocation plans to create the powerful, cost effective survey sample design for your study. It covers a wide range of sampling methods simple random sampling, stratified sampling and cluster sampling. The book also describes the mathematics involved behind the confidence limits, ratio estimation, sample size and survey precision. Small area estimation, randomized response, network, adaptive sampling, control sampling and permanent random numbers are also discussed in addition to most of the classical topics.
Author | : Arijit Chaudhuri |
Publisher | : Springer Nature |
Total Pages | : 273 |
Release | : 2022-05-08 |
Genre | : Mathematics |
ISBN | : 9811914184 |
As a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation. The book focuses on a wide range of topics which included Bayesian and Empirical Bayesian approaches, complex procedures of stratification, clustering, sampling in multi stages and phases, linear and non-linear estimation of parameters, small area estimation by spatial and chronological modelling, network and adaptive sampling methods and more. The book includes detailed case studies and exercises, making it valuable for students of statistics, specifically survey sampling.