教師資料查詢 | 類別: 期刊論文 | 教師: 黃文濤 HUANG, WEN-TAO (瀏覽個人網頁)

標題:Bayesian semiparametric regression analysis of multicategorical time-space data
學年89
學期2
出版(發表)日期2001/03/01
作品名稱Bayesian semiparametric regression analysis of multicategorical time-space data
作品名稱(其他語言)
著者Huang, Wen-tao; 黃文濤(等)
單位淡江大學經營決策學系
出版者
著錄名稱、卷期、頁數The annals of the institute of statistical mathemetics 53(1), pp.11-30
摘要We present a unified semiparametric Bayesian approach based on Markov random field priors for analyzing the dependence of multicategorical response variables on time, space and further covariates. The general model extends dynamic, or state space, models for categorical time series and longitudinal data by including spatial effects as well as nonlinear effects of metrical covariates in flexible semiparametric form. Trend and seasonal components, different types of covariates and spatial effects are all treated within the same general framework by assigning appropriate priors with different forms and degrees of smoothness. Inference is fully Bayesian and uses MCMC techniques for posterior analysis. The approach in this paper is based on latent semiparametric utility models and is particularly useful for probit models. The methods are illustrated by applications to unemployment data and a forest damage survey.
關鍵字Categorical time-space data;forest damage;latent utility models;Markov random fields;MCMC;probit models;semiparametric Bayesian inference;unemployment
語言英文
ISSN0020-3157;1572-9052
期刊性質國內
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國別德國
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