基于分层贝叶斯分析的残疾率小域估计方法

统计研究 ›› 2010, Vol. 27 ›› Issue (3): 83-88.

基于分层贝叶斯分析的残疾率小域估计方法

刘乐平潘松权任晓美

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-03-15 发布日期:2010-03-15

Small Area Estimation of Disability Based on Hierarchical Bayesian Statistics

Liu Leping , Pan Songquan , Ren Xiaomei

Received:1900-01-01 Revised:1900-01-01 Online:2010-03-15 Published:2010-03-15

摘要/Abstract

摘要： 小域估计（Small Area Estimation）是抽样调查领域里一个重要的研究方向，国计民生中的许多重要问题如失业率、传染病的发病率和民意测验等抽样调查都需要采用不同的小域估计方法。本文针对小域估计问题，以估计方法发展脉络为主线，以分层贝叶斯分析的小域估计为重点，对小域估计问题的理论、方法和最新进展进行简述，并利用澳大利亚残疾、老龄化和护理者（SDAC 2003）抽样调查实际数据，从分层贝叶斯分析角度对澳大利亚残疾率进行估计，最后对估计结果进行比较和讨论。

关键词: 分层贝叶斯分析, 小域估计, 残疾率

Abstract: Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics from both public and private sectors. In this paper，the theory and method of Small area estimation (SAE) are reviewed, then the recent developments of small area estimation are summarized. Finally, applying the Hierarchical Bayesian(HB) approach, the empirical analysis of this paper is based on knowledge and experience derived from a study of the incidence of disability in Australia. This study uses data from the Survey of Disability, Ageing and Carers (SDAC,2003).

Key words: Hierarchical Bayesian Statistics, Small Area Estimation, Disability

刘乐平潘松权任晓美. 基于分层贝叶斯分析的残疾率小域估计方法 [J]. 统计研究, 2010, 27(3): 83-88.

Liu Leping, Pan Songquan, Ren Xiaomei. Small Area Estimation of Disability Based on Hierarchical Bayesian Statistics[J]. Statistical Research, 2010, 27(3): 83-88.

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