crch: Censored Regression with Conditional Heteroscedasticity

Different approaches to censored or truncated regression with conditional heteroscedasticity are provided. First, continuous distributions can be used for the (right and/or left censored or truncated) response with separate linear predictors for the mean and variance. Second, cumulative link models for ordinal data (obtained by interval-censoring continuous data) can be employed for heteroscedastic extended logistic regression (HXLR). In the latter type of models, the intercepts depend on the thresholds that define the intervals.

Version: 1.0-4
Depends: R (≥ 2.10.0)
Imports: stats, Formula, ordinal, sandwich, scoringRules
Suggests: glmx, lmtest, memisc
Published: 2019-09-03
Author: Jakob Messner ORCID iD [aut, cre], Achim Zeileis ORCID iD [aut], Reto Stauffer ORCID iD [aut]
Maintainer: Jakob Messner <jakob.messner at>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Citation: crch citation info
Materials: NEWS
In views: Econometrics
CRAN checks: crch results


Reference manual: crch.pdf
Vignettes: Heteroscedastic Censored and Truncated Regression with crch
Package source: crch_1.0-4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: crch_1.0-4.tgz, r-oldrel: crch_1.0-4.tgz
Old sources: crch archive

Reverse dependencies:

Reverse imports: MortalityGaps
Reverse suggests: ensemblepp, insight, NetSimR, scoringRules
Reverse enhances: prediction


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