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Heteroscedastic censored and truncated regression with crch

  • Jakob W. Messner
  • , Georg J. Mayr
  • , Achim Zeileis
  • University of Innsbruck

Research output: Contribution to journal › Journal article › Research › peer-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
ISSN2073-4859
DOIs
Publication statusPublished - 2016
Externally publishedYes

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