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.

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Package details

AuthorAchim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Jakob W. Messner [aut] (<https://orcid.org/0000-0002-1027-3673>), Reto Stauffer [aut] (<https://orcid.org/0000-0002-3798-5507>), Ioannis Kosmidis [ctb] (<https://orcid.org/0000-0003-1556-0302>), Georg J. Mayr [ctb] (<https://orcid.org/0000-0001-6661-9453>)
MaintainerAchim Zeileis <Achim.Zeileis@R-project.org>
LicenseGPL-2 | GPL-3
Version1.2-1
URL https://topmodels.R-Forge.R-project.org/crch/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("crch")

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crch documentation built on Sept. 30, 2024, 9:22 a.m.