文章基本信息

标题：carx: an R Package to Estimate Censored Autoregressive Time Series with Exogenous Covariates
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作者：Chao Wang ; Kung-Sik Chan
期刊名称：R News
印刷版ISSN：1609-3631
出版年度：2017
卷号：9
期号：2
页码：213-231
语种：English
出版社：The R Foundation for Statistical Computing
摘要：We implement in the R package carx a novel and computationally efficient quasi-likelihood method for estimating a censored autoregressive model with exogenous covariates. The proposed quasi-likelihood method reduces to maximum likelihood estimation in absence of censoring. The carx package contains many useful functions for practical data analysis with censored stochastic regression, including functions for outlier detection, model diagnostics, and prediction with censored time series data. We illustrate the capabilities of the carx package with simulations and an elaborate real data analysis.