文章基本信息

标题：A Simple Class of Bayesian Nonparametric Autoregression Models
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作者：Maria Anna Di Lucca ; Alessandra Guglielmi ; Peter Müller 等
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2013
卷号：8
期号：1
页码：63-88
DOI：10.1214/13-BA803
语种：English
出版社：International Society for Bayesian Analysis
摘要：We introduce a model for a time series of continuous outcomes, that can be expressed as fully nonparametric regression or density regression on lagged terms. The model is based on a dependent Dirichlet process prior on a family of random probability measures indexed by the lagged covariates. The approach is also extended to sequences of binary responses. We discuss implementation and applications of the models to a sequence of waiting times between eruptions of the Old Faithful Geyser, and to a dataset consisting of sequences of recurrence indicators for tumors in the bladder of several patients.