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Author : En-Tzu Tang
Publisher :
ISBN 13 :
Total Pages : 228 pages
Book Rating : 4.:/5 (8 download)
Download or read book On Estimation of the Mean Squared Error in Small Area Estimation and Related Topics written by En-Tzu Tang and published by . This book was released on 2008 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Asian Development Bank
Publisher : Asian Development Bank
ISBN 13 : 9292622234
Total Pages : 152 pages
Book Rating : 4.2/5 (926 download)
Download or read book Introduction to Small Area Estimation Techniques written by Asian Development Bank and published by Asian Development Bank. This book was released on 2020-05-01 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Junyuan Wang
Publisher :
ISBN 13 :
Total Pages : 238 pages
Book Rating : 4.:/5 (467 download)
Download or read book Topics in Small Area Estimation with Applications to the National Resources Inventory written by Junyuan Wang and published by . This book was released on 2000 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical application of small area estimation in the National Resources Inventory, a large survey of the non-federal land area in the United States, is described. Several estimation issues raised by this application are discussed as motivation for theoretical investigation of some aspects of small area estimation. The situation in which individual small area sampling variances are directly estimated is studied. This situation is not covered by standard asymptotic results (Prasad and Rao (1990)), which assume that a finite-dimensional parameter characterizes the small area variances. An approximation for the mean square error (MSE) of the empirical best linear unbiased predictor and an estimator of the MSE are developed. Simulation studies show that the theoretical expressions are good approximations for the MSE of the predictors. Also the suggested MSE estimator has smaller overestimation for the MSE than related estimators in the literature when the between-area variance component is small. Small area estimation under a restriction, which forces small area estimates to sum to the direct estimate for a large area, is discussed. A criterion that unifies the derivation of several restricted estimators is proposed. The estimator that is the unique best linear unbiased estimator under the criterion is derived and an approximation for the MSE of the restricted estimator is presented. The bias of the empirical best linear unbiased predictor is assessed for the model in which the sampling errors are not normally distributed. The robustness of the MSE estimator is examined under non-normal error distributions by using simulations. The simulations also demonstrate that imposing a restriction can reduce the bias when the errors are not symmetrically distributed.
Author : Parimal Mukhopadhyay
Publisher : Alpha Science International, Limited
ISBN 13 :
Total Pages : 252 pages
Book Rating : 4.E/5 ( download)
Download or read book Small Area Estimation in Survey Sampling written by Parimal Mukhopadhyay and published by Alpha Science International, Limited. This book was released on 1998 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic exposition of the problems and procedures in producing statistics for small areas (districts, subdivisions, municipal areas; batches of industrial products) which have been lying scattered over different journals over the last three decades. The motivations of the different procedures have been explained, the promising results have been emphasized and the new research areas are indicated. The manner of exposition has been tried to be made lucid. The book will generate further interest in the area and would be helpful to the researchers and the survey statisticians working in this field.
Author : Elaheh Torkashvand
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)
Download or read book On Small Area Estimation Problems with Measurement Errors and Clustering written by Elaheh Torkashvand and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we first develop new statistical methodologies for small area estimation problems with measurement errors. The prediction of small area means for the unit-level regression model with the functional measurement error in the area-specific covariate is considered. We obtain the James-Stein (JS) estimate of the true area-specific covariate. Consequently, we construct the pseudo Bayes (PB) and pseudo empirical Bayes (PEB) predictors of small area means and estimate the mean squared prediction error (MSPE) associated with each predictor. Secondly, we modify the point estimation of the true area-specific covariate obtained earlier such that the histogram of the predictors of the small area means gets closer to its true one. We propose the constrained Bayes (CB) estimate of the true area-specific covariate. We show the superiority of the CB over the maximum likelihood (ML) estimate in terms of the Bayes risk. We also show the PB predictor of the small area mean based on the CB estimate of the true area-specific covariate dominates its counterpart based on the ML estimate in terms of the Bayes risk. We compare the performance of different predictors of the small area means using measures such as sensitivity, specificity, positive predictive value, negative predictive value, and MSPE. We believe that using the PEB and pseudo hierarchical Bayes predictors of small area means based on the constrained empirical Bayes (CEB) and constrained hierarchical Bayes (CHB) offers higher precision in recognizing socio-economic groups which are in danger of the prehypertension. Clustering the small areas to understand the behavior of the random effects better and accordingly, to predict the small area means is the final problem we address. We consider the Fay-Herriot model for this problem. We design a statistical test to evaluate the assumption of the equality of the variance components in different clusters. In the case of rejection of the null hypothesis of the equality of the variance components, we implement a modified version of Tukey's method. We calculate the MSPE to evaluate the effect of the clustering on the precision of predictors of the small area means. We apply our methodologies to real data sets.
Author : J. N. K. Rao
Publisher : John Wiley & Sons
ISBN 13 : 111873579X
Total Pages : 476 pages
Book Rating : 4.1/5 (187 download)
Download or read book Small Area Estimation written by J. N. K. Rao and published by John Wiley & Sons. This book was released on 2015-08-10 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Shonosuke Sugasawa
Publisher : Springer Nature
ISBN 13 : 9811994862
Total Pages : 127 pages
Book Rating : 4.8/5 (119 download)
Download or read book Mixed-Effects Models and Small Area Estimation written by Shonosuke Sugasawa and published by Springer Nature. This book was released on 2023-02-02 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects prediction, variable selection, and asymptotic theory, are introduced. Standard mixed-effects models used in small area estimation, known as the Fay-Herriot model and the nested error regression model, are then introduced. Both frequentist and Bayesian approaches are given to compute predictors of small area parameters of interest. For measuring uncertainty of the predictors, several methods to calculate mean squared errors and confidence intervals are discussed. Various advanced approaches using mixed-effects models are introduced, from frequentist to Bayesian approaches. This book is helpful for researchers and graduate students in fields requiring data analysis skills as well as in mathematical statistics.
Author : J. Andrew Royle
Publisher : Elsevier
ISBN 13 : 0080559255
Total Pages : 463 pages
Book Rating : 4.0/5 (85 download)
Download or read book Hierarchical Modeling and Inference in Ecology written by J. Andrew Royle and published by Elsevier. This book was released on 2008-10-15 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution* abundance models based on many sampling protocols, including distance sampling* capture-recapture models with individual effects* spatial capture-recapture models based on camera trapping and related methods* population and metapopulation dynamic models* models of biodiversity, community structure and dynamics - Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) - Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis - Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS - Computing support in technical appendices in an online companion web site
Author : Nicholas T. Longford
Publisher : Springer Science & Business Media
ISBN 13 : 9781852337605
Total Pages : 384 pages
Book Rating : 4.3/5 (376 download)
Download or read book Missing Data and Small-Area Estimation written by Nicholas T. Longford and published by Springer Science & Business Media. This book was released on 2005-08-05 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?rst C- pion Fellow (2000–2002). For the Fellowship I proposed these two topics as areas in which the academic statistics could contribute to the development of government statistics, in exchange for access to the operational details and background that would inform the direction and sharpen the focus of a- demic research. After a few years of involvement, I have come to realise that the separation of ‘academic’ and ‘industrial’ statistics is not well suited to either party, and their integration is the key to progress in both branches. Most of the work on this monograph was done while I was a visiting l- turer at Massey University, Palmerston North, New Zealand. The hospitality and stimulating academic environment of their Institute of Information S- ence and Technology is gratefully acknowledged. I could not name all those who commented on my lecture notes and on the presentations themselves; apart from them, I want to thank the organisers and silent attendees of all the events, and, with a modicum of reluctance, the ‘grey ?gures’ who kept inquiring whether I was any nearer the completion of whatever stage I had been foolish enough to attach a date.
Author :
Publisher :
ISBN 13 :
Total Pages : 296 pages
Book Rating : 4.3/5 (91 download)
Download or read book Synthetic Estimates for Small Areas written by and published by . This book was released on 1979 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Domingo Morales
Publisher : Springer Nature
ISBN 13 : 3030637573
Total Pages : 606 pages
Book Rating : 4.0/5 (36 download)
Download or read book A Course on Small Area Estimation and Mixed Models written by Domingo Morales and published by Springer Nature. This book was released on 2021-03-12 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.
Author : Monica Pratesi
Publisher : John Wiley & Sons
ISBN 13 : 1118815017
Total Pages : 485 pages
Book Rating : 4.1/5 (188 download)
Download or read book Analysis of Poverty Data by Small Area Estimation written by Monica Pratesi and published by John Wiley & Sons. This book was released on 2016-02-23 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to implementing SAE methods for poverty studies and poverty mapping There is an increasingly urgent demand for poverty and living conditions data, in relation to local areas and/or subpopulations. Policy makers and stakeholders need indicators and maps of poverty and living conditions in order to formulate and implement policies, (re)distribute resources, and measure the effect of local policy actions. Small Area Estimation (SAE) plays a crucial role in producing statistically sound estimates for poverty mapping. This book offers a comprehensive source of information regarding the use of SAE methods adapted to these distinctive features of poverty data derived from surveys and administrative archives. The book covers the definition of poverty indicators, data collection and integration methods, the impact of sampling design, weighting and variance estimation, the issue of SAE modelling and robustness, the spatio-temporal modelling of poverty, and the SAE of the distribution function of income and inequalities. Examples of data analyses and applications are provided, and the book is supported by a website describing scripts written in SAS or R software, which accompany the majority of the presented methods. Key features: Presents a comprehensive review of SAE methods for poverty mapping Demonstrates the applications of SAE methods using real-life case studies Offers guidance on the use of routines and choice of websites from which to download them Analysis of Poverty Data by Small Area Estimation offers an introduction to advanced techniques from both a practical and a methodological perspective, and will prove an invaluable resource for researchers actively engaged in organizing, managing and conducting studies on poverty.
Author : Jan Pablo Burgard
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (116 download)
Download or read book Area-level Small Area Estimation with Missing Values written by Jan Pablo Burgard and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-based small area predictors are derived under the assumption that data files are complete. In application to real data, files may contain missing values. We introduce a variant of the bivariate Fay-Herriot model that takes into account for missing values in one component of the target variable and give fitting algorithms to estimate the model parameters. Based on the new model, we introduce empirical best predictors of domain means and derive an approximation to the mean squared error.
Author : George A. F. Seber
Publisher : John Wiley & Sons
ISBN 13 : 0470226781
Total Pages : 592 pages
Book Rating : 4.4/5 (72 download)
Download or read book A Matrix Handbook for Statisticians written by George A. F. Seber and published by John Wiley & Sons. This book was released on 2008-01-28 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and statistical theory, this handbook is organized by topic rather than mathematical developments and includes numerous references to both the theory behind the methods and the applications of the methods. A uniform approach is applied to each chapter, which contains four parts: a definition followed by a list of results; a short list of references to related topics in the book; one or more references to proofs; and references to applications. The use of extensive cross-referencing to topics within the book and external referencing to proofs allows for definitions to be located easily as well as interrelationships among subject areas to be recognized. A Matrix Handbook for Statisticians addresses the need for matrix theory topics to be presented together in one book and features a collection of topics not found elsewhere under one cover. These topics include: Complex matrices A wide range of special matrices and their properties Special products and operators, such as the Kronecker product Partitioned and patterned matrices Matrix analysis and approximation Matrix optimization Majorization Random vectors and matrices Inequalities, such as probabilistic inequalities Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumes a fundamental knowledge of vectors and matrices, maintains a reasonable level of abstraction when appropriate, and provides a comprehensive compendium of linear algebra results with use or potential use in statistics. A Matrix Handbook for Statisticians is an essential, one-of-a-kind book for graduate-level courses in advanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves as an excellent self-study guide for statistical researchers.
Author : Jiming Jiang
Publisher : CRC Press
ISBN 13 : 1498700462
Total Pages : 252 pages
Book Rating : 4.4/5 (987 download)
Download or read book Asymptotic Analysis of Mixed Effects Models written by Jiming Jiang and published by CRC Press. This book was released on 2017-09-19 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis.
Author : Robert Tanton
Publisher : Springer Science & Business Media
ISBN 13 : 9400746237
Total Pages : 272 pages
Book Rating : 4.4/5 (7 download)
Download or read book Spatial Microsimulation: A Reference Guide for Users written by Robert Tanton and published by Springer Science & Business Media. This book was released on 2012-11-13 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.
Author : J. Sunil Rao
Publisher : CRC Press
ISBN 13 : 1000905098
Total Pages : 298 pages
Book Rating : 4.0/5 (9 download)
Download or read book Statistical Methods in Health Disparity Research written by J. Sunil Rao and published by CRC Press. This book was released on 2023-07-11 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Presents an overview of methods and applications of health disparity estimation • First book to synthesize research in this field in a unified statistical framework • Covers classical approaches, and builds to more modern computational techniques • Includes many worked examples and case studies using real data • Discusses available software for estimation
