Jiming Jiang, J. Sunil Rao

Robust Small Area Estimation (eBook, ePUB)

Methods, Theory, Applications, and Open Problems

• Format: ePub

Produktbeschreibung

Intended to provide a nearly comprehensive account of methods, theory, applications, as well as open problems related to robust SAE, that the monograph will help persuade practitioners, such as those in government agencies, to more readily adopt robust SAE methods.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 20. August 2025
• Englisch
• ISBN-13: 9781040398814
• Artikelnr.: 74414850

Autorenporträt

Jiming Jiang is a Professor of Statistics and Chair of the Department of Statistics at the University of California, Davis. His research interests include mixed effects models, small area estimation, model selection, statistical genetics/bioinformatics, and asymptotic theory. He is author of over 100 peer-reviewed publications and six books/monographs, including Linear and Generalized Linear Mixed Models and Their Applications (Springer 2007, 2nd ed. 2021), Large Sample Techniques for Statistics (Springer 2010, 2nd ed. 2022), The Fence Methods (World Scientific 2015; joint with Nguyen), Asymptotic Analysis of Mixed Effects Models: Theory, Application, and Open Problems (Chapman & Hall/CRC, 2017), Robust Mixed Model Analysis (World Scientific 2019), and Robust Small Area Estimation: Methods, Theory, Applications and Open Problems (Chapman & Hall/CRC, 2025; joint with Rao). He has served editorial boards of several major statistical journals including the Annals of Statistics and Journal of the American Statistical Association. He is a Fellow of the American Association for the Advancement of Science, a Fellow of the American Statistical Association (ASA), a Fellow of the Institute of Mathematical Statistics, and an Elected Member of the International Statistical Institute. He is a co-recipient of Outstanding Statistical Application Award (ASA, 1998), a (first) co-recipient of Distinguished Alumni Award (National Institute of Statistical Sciences, 2015), a Yangtze River Scholar (Chaired Professor, 2017-2020), a Primary Speaker of the Morris Hansen Lecture (Washington Statistical Society, 2023), and a recipient of the Award for Outstanding Contribution to Small Area Estimation (the SAE Award, 2024).

J. Sunil Rao is Professor in the Division of Biostatistics and Health Data Science at the University of Minnesota, Twin Cities. He is also the Director of Biostatistics at the Masonic Cancer Center and Founding Chair and Professor Emeritus in the Division of Biostatistics at the University of Miami. His research interests include mixed modelling, small area estimation, high dimensional data analysis, modelling of cancer genomic data and statistical methods for health disparity research. He is author of over 100 peer-reviewed publications and two books/monographs, including Statistical Methods in Health Disparity Research (Chapman & Hall/CRC, 2023) and Robust Small Area Estimation: Methods, Theory, Applications and Open Problems (Chapman & Hall/CRC, 2025; joint with Jiang). He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and an Elected Member of the International Statistical Institute. He has served as an Associate Editor for a number of different statistical journals. He received the V.K. Gupta Endowment Award for Achievements in Statistical Thinking and Practice (2024) and was appointed as an Honorary Member of the Society for Statistics, Computers and Applications (2024).

Inhaltsangabe

1. Small Area Estimation: A Brief Overview. 2. SAE Methods Built on Weaker
Assumptions. 3. Outlier Robustness. 4. Observed Best Prediction and Its
Extensions. 5. More Flexible Models. 6. Model Selection and Diagnostics. 7.
Other Topics.