Bayesian Demographic Estimation and Forecasting

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John Bryant Junni L. Zhang (Peking University, Haidian District, Beijing, People's Republic of China)

Bayesian Demographic Estimation and Forecasting

John Bryant, Junni L. Zhang (Peking University, Haidian District, Beijing, People's Republic of China)

$221

Hardback

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English

Chapman & Hall/CRC
03 July 2018

Social forecasting, future studies

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: John Bryant, Junni L. Zhang (Peking University, Haidian District, Beijing, People's Republic of China)
Imprint: Chapman & Hall/CRC
Country of Publication: United States
Dimensions: Height: 234mm, Width: 156mm,
Weight: 584g
ISBN: 9781498762625
ISBN 10: 149876262X
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
Pages: 280
Publication Date: 03 July 2018
Audience: Professional and scholarly , Undergraduate
Format: Hardback
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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Bayesian Demographic Estimation and Forecasting

John Bryant, Junni L. Zhang (Peking University, Haidian District, Beijing, People's Republic of China)

$221

Hardback

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