Global estimation and scenario-based projections of sex ratio at birth and missing female births using a Bayesian hierarchical time series mixture model-Reference-Cited by-同舟云学术

Global estimation and scenario-based projections of sex ratio at birth and missing female births using a Bayesian hierarchical time series mixture model

Published:2021-09-01 Issue:3 Volume:15 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Chao Fengqing¹,Gerland Patrick²,Cook Alex R.³,Alkema Leontine⁴

Affiliation:

1. Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology

2. United Nations Population Division, DESA, United Nations

3. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System

4. School of Public Health and Health Sciences, University of Massachusetts, Amherst

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

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