Art

J-GLOBAL ID：202002234698767178   Reference number：20A0969375

Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous-discrete covariates

混合連続離散共変量を欠く回帰モデルに対するセミパラメトリックBayes多重帰属

Author (3)： Kato Ryo (Research Institute for Economics and Business Administration, Kobe University, Kobe, Japan) ,  Hoshino Takahiro (Department of Economics, Keio University, Tokyo, Japan) ,  Hoshino Takahiro (RIKEN Center for Advanced Intelligence Project, Tokyo, Japan)
Material： Annals of the Institute of Statistical Mathematics  (Ann Inst Stat Math)
Volume： 72  Issue： 3  Page： 803-825  Publication year： Jun. 2020 
JST Material Number： W2286A  ISSN： 0020-3157  Document type： Article
Article type： 原著論文  Country of issue： Germany, Federal Republic of (DEU)  Language： ENGLISH (EN)

Thesaurus term： *regression model ,  *statistical analysis ,  stochastic model ,  *Bayes estimation ,  measurement data ,  compatibility (property) ,  Alzheimer Disease ,  missing data ,  mathematical model
Semi thesaurus term： Alzheimer's disease ,  semiparametric model ,  *covariate ,  missing data

Author keywords (5)： Full conditional specification ,  Missing data ,  Multiple imputation ,  Probit stick-breaking process mixture ,  Semiparametric Bayes model

JST classification (2)： Statistics  (AB08000H) ,  Applied mathematics  (AB11000P)

Terms in the title (3)： 共変量 ,  回帰モデル ,  多重