Heteroscedastic censored and truncated regression with crch

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

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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 left- or 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).

Original languageEnglish
JournalR Journal
Volume8
Issue number1
Pages (from-to)173-181
Number of pages9
Publication statusPublished - 2016
Externally publishedYes

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