Robust Small Area Estimation
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Robust Small Area Estimation
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Author : Jiming Jiang
language : en
Publisher: CRC Press
Release Date : 2025-08-20
Robust Small Area Estimation written by Jiming Jiang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-20 with Mathematics categories.
In recent years there has been substantial and growing interest in small area estimation (SAE) that is largely driven by practical demands. Here, the term "small area" typically refers to a subpopulation or domain of interest for which a reliable direct estimate, based only on the domain-specific sample, cannot be produced due to small sample size in the domain. Keywords in SAE are “borrowing strength”. Because there are insufficient samples from the small areas to produce reliable direct estimates, statistical methods are sought to utilize other sources of information to do better than the direct estimates. A typical way of borrowing strength is via statistical modelling. On the other hand, there is no “free lunch”. Yes, one can do better by borrowing strength, but there is a cost. This is the main topic discussed in this text. Features A comprehensive account of methods, applications, as well as some open problems related to robust SAE Methods illustrated by worked examples and case studies using real data Discusses some advanced topics including benchmarking, Bayesian approaches, machine learning methods, missing data, and classified mixed model prediction Supplemented with code and data via a website Robust Small Area Estimation: Methods, Applications, and Open Problems is primarily aimed at researchers and graduate students of statistics and data science and would also be suitable for geography and survey methodology researchers. The practical approach should help persuade practitioners, such as those in government agencies, to more readily adopt robust SAE methods. It could be used to teach a graduate-level course to students with a background in mathematical statistics.
Robust Small Area Estimation Under Spatial Non Stationarity
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Author :
language : en
Publisher:
Release Date : 2016
Robust Small Area Estimation Under Spatial Non Stationarity written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Geographically weighted small area methods have been studied in literature for small area estimation. Although these approaches are useful for the estimation of small area means efficiently under strict parametric assumptions, they can be very sensitive to outliers in the data. In this paper, we propose a robust extension of the geographically weighted empirical best linear unbiased predictor (GWEBLUP). In particular, we introduce robust projective and predictive small area estimators under spatial non-stationarity. Mean squared error estimation is performed by two different analytic approaches that account for the spatial structure in the data. The results from the model-based simulations indicate that the proposed approach may lead to gains in terms of efficiency. Finally, the methodology is demonstrated in an illustrative application for estimating the average total cash costs for farms in Australia.
Small Area Estimation
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Author : J. N. K. Rao
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-24
Small Area Estimation written by J. N. K. Rao and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-24 with Mathematics categories.
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.
Analysis Of Poverty Data By Small Area Estimation
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Author : Monica Pratesi
language : en
Publisher: John Wiley & Sons
Release Date : 2016-02-23
Analysis Of Poverty Data By Small Area Estimation written by Monica Pratesi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-23 with Mathematics categories.
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.
Small Area Estimation And Microsimulation Modeling
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Author : Azizur Rahman
language : en
Publisher: CRC Press
Release Date : 2016-11-30
Small Area Estimation And Microsimulation Modeling written by Azizur Rahman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Mathematics categories.
Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.
Mixed Effects Models And Small Area Estimation
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Author : Shonosuke Sugasawa
language : en
Publisher: Springer Nature
Release Date : 2023-02-02
Mixed Effects Models And Small Area Estimation written by Shonosuke Sugasawa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-02 with Mathematics categories.
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.
Robust Small Area Estimation
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Author : Lixia Diao
language : en
Publisher:
Release Date : 2008
Robust Small Area Estimation written by Lixia Diao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Small Area Estimation In Forest Inventories New Needs Methods And Tools
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Author : Barry Wilson
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-17
Small Area Estimation In Forest Inventories New Needs Methods And Tools written by Barry Wilson and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-17 with Science categories.
Contributions To Sampling Statistics
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Author : Fulvia Mecatti
language : en
Publisher: Springer
Release Date : 2014-06-02
Contributions To Sampling Statistics written by Fulvia Mecatti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-02 with Business & Economics categories.
This book contains a selection of the papers presented at the ITACOSM 2013 Conference, held in Milan in June 2013. It is intended as an international forum of scientific discussion on the developments of theory and application of survey sampling methodologies and applications in human and natural sciences. The book gathers research papers carefully selected from both invited and contributed sessions of the conference. The whole book appears to be a relevant contribution to various key aspects of sampling methodology and techniques; it deals with some hot topics in sampling theory, such as calibration, quantile-regression and multiple frame surveys and with innovative methodologies in important topics of both sampling theory and applications. Contributions cut across current sampling methodologies such as interval estimation for complex samples, randomized responses, bootstrap, weighting, modeling, imputation, small area estimation and effective use of auxiliary information; applications cover a wide and enlarging range of subjects in official household surveys, Bayesian networks, auditing, business and economic surveys, geostatistics and agricultural statistics. The book is an updated, high level reference survey addressed to researchers, professionals and practitioners in many fields.
Poverty And Social Exclusion
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Author : Gianni Betti
language : en
Publisher: Routledge
Release Date : 2013-07-18
Poverty And Social Exclusion written by Gianni Betti and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-18 with Business & Economics categories.
Poverty and inequality remain at the top of the global economic agenda, and the methodology of measuring poverty continues to be a key area of research. This new book, from a leading international group of scholars, offers an up to date and innovative survey of new methods for estimating poverty at the local level, as well as the most recent multidimensional methods of the dynamics of poverty. It is argued here that measures of poverty and inequality are most useful to policy-makers and researchers when they are finely disaggregated into small geographic units. Poverty and Social Exclusion: New Methods of Analysis is the first attempt to compile the most recent research results on local estimates of multidimensional deprivation. The methods offered here take both traditional and multidimensional approaches, with a focus on using the methodology for the construction of time-related measures of deprivation at the individual and aggregated levels. In analysis of persistence over time, the book also explores whether the level of deprivation is defined in terms of relative inequality in society, or in relation to some supposedly absolute standard. This book is of particular importance as the continuing international economic and financial crisis has led to the impoverishment of segments of population as a result of unemployment, bankruptcy, and difficulties in obtaining credit. The volume will therefore be of interest to all those working on economic, econometric and statistical methods and empirical analyses in the areas of poverty, social exclusion and income inequality.