carx: an R Package to Estimate Censored Autoregressive Time Series with Exogenous Covariates

Abstract 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.