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. Infrastructure for working with censored or truncated normal, logistic, and Student-t distributions, i.e., d/p/q/r functions and distributions3 objects.

Version: 1.1-1
Depends: R (≥ 3.6.0)
Imports: stats, Formula, ordinal, sandwich, scoringRules
Suggests: distributions3 (≥ 0.2.1), glmx, lmtest, memisc
Published: 2022-09-09
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: Distributions, Econometrics
CRAN checks: crch results


Reference manual: crch.pdf
Vignettes: Heteroscedastic Censored and Truncated Regression with crch


Package source: crch_1.1-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): crch_1.1-1.tgz, r-oldrel (arm64): crch_1.1-1.tgz, r-release (x86_64): crch_1.1-1.tgz, r-oldrel (x86_64): crch_1.1-1.tgz
Old sources: crch archive

Reverse dependencies:

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


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