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).
dglm, glmx, gamlss, betareg, crch, Formula, gamlss.cens, gamlss.tr, sampleSelection, mhurdle
Econometrics, Psychometrics, SocialSciences, Survival
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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
@article{RJ-2016-012,
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}
}