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	Bayesian computation for contingency tables with incomplete cell-counts
	Tian, GL ; Ng, KW ; Geng, Z
	2003
关键词	Bayesian inference grouped and nested Dirichlet distributions incomplete data inverse Bayes formulae stochastic representation CATEGORICAL-DATA MARGINAL DENSITIES NONRESPONSE MODELS
英文摘要	This article studies Bayesian analysis of contingency tables (or multinomial data) where the cell counts are not fully observed due to reasons such as nonresponse and misclassification, and derives the posterior distributions of the unknown cell probabilities in terms of various types of generalized Dirichlet distributions. For some special situations such as grouped and nested Dirichlet distributions, the posterior means of the unknown cell probabilities can be obtained in closed form by using inverse Bayes formulae and/or stochastic representation. When closed-form expressions do not exist, we suggest using importance sampling with a feasible proposal density to approximately compute the posterior quantities, and propose a procedure for choosing an effective proposal density. Applications are illustrated by sample surveys with nonresponse, crime survey data, death penalty attitude data, and misclassified multinomial data.; Statistics & Probability; SCI(E); 15; ARTICLE; 1; 189-206; 13
语种	英语
出处	SCI
出版者	statistica sinica
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/400996]
专题	数学科学学院
推荐引用方式 GB/T 7714	Tian, GL,Ng, KW,Geng, Z. Bayesian computation for contingency tables with incomplete cell-counts. 2003-01-01.

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