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Bayesian Demographic Estimation and Forecasting by John Bryant at Abbey's Bookshop,
Bayesian Demographic Estimation and Forecasting
— —
John Bryant Junni L. Zhang

Bayesian Demographic Estimation and Forecasting

John Bryant,  Junni L. Zhang

$98.99

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English
Chapman & Hall/CRC
30 June 2020
Psychological methodology; Epidemiology & medical statistics; Probability & statistics
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting. The frameworks draw on recent advances in statistical methodology to provide new tools for tackling challenges such as disaggregation, measurement error, missing data, and combining multiple data sources. The methods apply to single demographic series, or to entire demographic systems. The methods unify estimation and forecasting, and yield detailed measures of uncertainty.

The book assumes minimal knowledge of statistics, and no previous knowledge of demography. The authors have developed a set of R packages implementing the methods. Data and code for all applications in the book are available on www.bdef-book.com.

""This book will be welcome for the scientific community of forecasters…as it presents a new approach which has already given important results and which, in my opinion, will increase its importance in the future."" ~Daniel Courgeau, Institut national d'études démographiques
By:   ,
Imprint:   Chapman & Hall/CRC
Country of Publication:   United Kingdom
Dimensions:   Height: 234mm,  Width: 156mm, 
Weight:   300g
ISBN:   9780367571368
ISBN 10:   0367571366
Series:   Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
Pages:   292
Publication Date:  
Audience:   College/higher education ,  General/trade ,  Primary ,  ELT Advanced
Format:   Paperback
Publisher's Status:   Active

John Bryant is a senior researcher at Statistics New Zealand. He has previously worked at the New Zealand Treasury, and at universities in New Zealand and Thailand. He has consulted for many international organizations, including UNICEF, the FAO, and the World Bank. His research interests include applied demography, data science, and Bayesian statistics. Junni L. Zhang is an associate professor of statistics at Guanghua School of Management, Peking University. Her research interests include Bayesian statistics, text mining, and causal inference. She has extensive experience teaching undergraduate, graduate, MBA and executive courses, and is the author of Data Mining and Its Applications (in Chinese).

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