The R Journal: article published in 2017, volume 9:2

carx: an R Package to Estimate Censored Autoregressive Time Series with Exogenous Covariates PDF download
Chao Wang and Kung-Sik Chan , The R Journal (2017) 9:2, pages 213-231.

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.

Received: 2017-03-10; online 2017-11-27, supplementary material, (2.3 Kb)
CRAN packages: censReg, AER, NADA, VGAM, MCMCpack, cents, ARCensReg, carx, xts, TSA
CRAN Task Views implied by cited CRAN packages: Survival, TimeSeries, Econometrics, Distributions, Multivariate, Psychometrics, Bayesian, Environmetrics, ExtremeValue, Finance, SocialSciences, SpatioTemporal


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2017-064,
  author = {Chao Wang and Kung-Sik Chan},
  title = {{carx: an R Package to Estimate Censored Autoregressive Time
          Series with Exogenous Covariates}},
  year = {2017},
  journal = {{The R Journal}},
  url = {https://journal.r-project.org/archive/2017/RJ-2017-064/index.html},
  pages = {213--231},
  volume = {9},
  number = {2}
}