Package: crch 1.2-0

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.

Authors:Achim Zeileis [aut, cre], Jakob W. Messner [aut], Reto Stauffer [aut], Ioannis Kosmidis [ctb], Georg J. Mayr [ctb]

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Bug tracker:https://r-forge.r-project.org/projects/topmodels

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40 exports 2.83 score 18 dependencies 2 dependents 1 mentions 87 scripts 3.0k downloads

Last updated 2 days agofrom:c3d408bceb. Checks:OK: 9. Indexed: no.

Exports:CensoredLogisticCensoredNormalCensoredStudentsTcrchcrch.boostcrch.boost.fitcrch.controlcrch.fitcrch.stabseldclogisdcnormdctdtlogisdtnormdttgetSummary.crchhxlrhxlr.controlpclogispcnormpctptlogisptnormpttqclogisqcnormqctqtlogisqtnormqttrclogisrcnormrctrtlogisrtnormrtttrchTruncatedLogisticTruncatedNormalTruncatedStudentsT

Dependencies:evaluateFormulahighrknitrlatticeMASSMatrixnlmenumDerivordinalRcppRcppArmadillosandwichscoringRulesucminfxfunyamlzoo