Heteroscedastic Censored and Truncated Regression with crch

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).

Jakob W. Messner , Georg J. Mayr , Achim Zeileis

CRAN packages used

dglm, glmx, gamlss, betareg, crch, Formula, gamlss.cens, gamlss.tr, sampleSelection, mhurdle

CRAN Task Views implied by cited packages

Econometrics, Psychometrics, SocialSciences, Survival


Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".


For attribution, please cite this work as

Messner, et al., "The R Journal: Heteroscedastic Censored and Truncated Regression with crch", The R Journal, 2015

BibTeX citation

  author = {Messner, Jakob W. and Mayr, Georg J. and Zeileis, Achim},
  title = {The R Journal: Heteroscedastic Censored and Truncated Regression with crch},
  journal = {The R Journal},
  year = {2015},
  note = {https://doi.org/10.32614/RJ-2016-012},
  doi = {10.32614/RJ-2016-012},
  volume = {8},
  issue = {1},
  issn = {2073-4859},
  pages = {173-181}