Mixed Effects Models And Small Area Estimation
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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.
A Course On Small Area Estimation And Mixed Models
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Author : Domingo Morales
language : en
Publisher: Springer Nature
Release Date : 2021-03-12
A Course On Small Area Estimation And Mixed Models written by Domingo Morales and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-12 with Social Science categories.
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.
Asymptotic Analysis Of Mixed Effects Models
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Author : Jiming Jiang
language : en
Publisher: CRC Press
Release Date : 2017-09-19
Asymptotic Analysis Of Mixed Effects Models 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 2017-09-19 with Mathematics categories.
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.
Small Area Estimation
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Author : J. N. K. Rao
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-25
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 2005-02-25 with Mathematics categories.
An accessible introduction to indirect estimation methods, both traditional and model-based. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation. Uses a basic area-level linear model to illustrate the methods Presents the various extensions including binary response data through generalized linear models and time series data through linear models that combine cross-sectional and time series features Provides recent applications of SAE including several in U.S. Federal programs Offers a comprehensive discussion of the design issues that impact SAE
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.
Mixed Effects Models And Small Area Estimation
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Author : Shonosuke Sugasawa
language : en
Publisher:
Release Date : 2023
Mixed Effects Models And Small Area Estimation written by Shonosuke Sugasawa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with 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.
Samhsa Substance Abuse In States And Metropolitan Areas Model Based Estimates From The 1991 1993 Nhsda Methodology Report Office Of Applied Studies Methodological Series M 1 June 1997
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Author :
language : en
Publisher:
Release Date : 1997
Samhsa Substance Abuse In States And Metropolitan Areas Model Based Estimates From The 1991 1993 Nhsda Methodology Report Office Of Applied Studies Methodological Series M 1 June 1997 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 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.
Missing Data And Small Area Estimation
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Author : Nicholas T. Longford
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-11-24
Missing Data And Small Area Estimation written by Nicholas T. Longford and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-24 with Mathematics categories.
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.
Statistical Learning And Modeling In Data Analysis
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Author : Simona Balzano
language : en
Publisher: Springer Nature
Release Date : 2021-07-13
Statistical Learning And Modeling In Data Analysis written by Simona Balzano and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with Mathematics categories.
The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.