The R Journal: article published in 2016, volume 8:1

Heteroscedastic Censored and Truncated Regression with crch
Jakob W. Messner, Georg J. Mayr and Achim Zeileis , The R Journal (2016) 8:1, pages 173-181.

Abstract The crch package provides functions for maximum likelihood estimation of censored or truncated regression models with conditional heteroscedasticity along with suitable standard methods to summarize the fitted models and compute predictions, residuals, etc. The supported distributions include leftor right-censored or truncated Gaussian, logistic, or student-t distributions with potentially different sets of regressors for modeling the conditional location and scale. The models and their R implementation are introduced and illustrated by numerical weather prediction tasks using precipitation data for Innsbruck (Austria).

Received: 2015-06-28; online 2015-10-14
CRAN packages: dglm, glmx, gamlss, betareg, crch, Formula, gamlss.cens, gamlss.tr, sampleSelection, mhurdle
CRAN Task Views implied by cited CRAN packages: Econometrics, Psychometrics, SocialSciences, Survival

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2016-012,
  author = {Jakob W. Messner and Georg J. Mayr and Achim Zeileis},
  title = {{Heteroscedastic Censored and Truncated Regression with crch}},
  year = {2016},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2016-012},
  url = {https://doi.org/10.32614/RJ-2016-012},
  pages = {173--181},
  volume = {8},
  number = {1}
}