Combining multiple imperfect data sources for small area estimation:a Bayesian model of provincial fertility rates in Cambodia  被引量:1

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作  者:Junni L.Zhang John Bryant 

机构地区:[1]Guanghua School of Management,Center for Statistical Science and Center for Data Science,Peking University,Beijing,People’s Republic of China [2]Bayesian Demography Limited,Christchurch,New Zealand

出  处:《Statistical Theory and Related Fields》2019年第2期178-185,共8页统计理论及其应用(英文)

摘  要:Demographic estimation becomes a problem of small area estimation when detaileddisaggregation leads to small cell counts.The usual difficulties of small area estimation are compounded when the available data sources contain measurement errors.We present a Bayesianapproach to the problem of small area estimation with imperfect data sources.The overall modelcontains separate submodels for underlying demographic processes and for measurement processes.All unknown quantities in the model,including coverage ratios and demographic rates,are estimated jointly via Markov chain Monte Carlo methods.The approach is illustrated usingthe example of provincial fertility rates in Cambodia.

关 键 词:Measurement error Bayesian hierarchical model coverage errors FERTILITY Cambodia small area estimation 

分 类 号:TN9[电子电信—信息与通信工程]

 

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