ARCensReg: Fitting Univariate Censored Linear Regression Model with Autoregressive Errors

It fits a univariate left, right, or interval censored linear regression model with autoregressive errors, considering the normal or the Student-t distribution for the innovations. It provides estimates and standard errors of the parameters, predicts future observations, and supports missing values on the dependent variable. References used for this package: Schumacher, F. L., Lachos, V. H., & Dey, D. K. (2017). Censored regression models with autoregressive errors: A likelihood-based perspective. Canadian Journal of Statistics, 45(4), 375-392 <doi:10.1002/cjs.11338>. Schumacher, F. L., Lachos, V. H., Vilca-Labra, F. E., & Castro, L. M. (2018). Influence diagnostics for censored regression models with autoregressive errors. Australian & New Zealand Journal of Statistics, 60(2), 209-229 <doi:10.1111/anzs.12229>. Valeriano, K. A., Schumacher, F. L., Galarza, C. E., & Matos, L. A. (2021). Censored autoregressive regression models with Student-t innovations. arXiv preprint <arXiv:2110.00224>.

Getting started

Package details

AuthorFernanda L. Schumacher [aut, cre] (<>), Katherine A. L. Valeriano [ctb] (<>), Victor H. Lachos [ctb] (<>), Christian G. Morales [ctb] (<>), Larissa A. Matos [ctb] (<>)
MaintainerFernanda L. Schumacher <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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ARCensReg documentation built on Aug. 30, 2023, 1:09 a.m.