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crch (version 1.0-4)

Censored Regression with Conditional Heteroscedasticity

Description

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.

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Version

Install

install.packages('crch')

Monthly Downloads

2,281

Version

1.0-4

License

GPL-2 | GPL-3

Maintainer

Jakob Messner

Last Published

September 3rd, 2019

Functions in crch (1.0-4)

crch.stabsel

Auxiliary functions to perform stability selection using boosting.
hxlr.control

Auxiliary Function for Controlling HXLR Fitting
predict.hxlr

Predict/Fitted Values for HXLR Fits
tlogis

The Truncated Logistic Distribution
crch.boost

Auxiliary functions to fit crch models via boosting.
tnorm

The Truncated Normal Distribution
tt

The Truncated Student-t Distribution
coef.hxlr

Methods for HXLR Objects
plot.crch.boost

Plot coefficient paths of boosted CRCH objects.
ct

The Censored Student-t Distribution
clogis

The Censored Logistic Distribution
hxlr

Heteroscedastic Extended Logistic Regression
predict.crch

Predicted/Fitted Values for CRCH Fits
predict.crch.boost

Predicted/Fitted Values for boosted CRCH Fits
RainIbk

Precipitation Observations and Forecasts for Innsbruck
crch.control

Auxiliary Function for Controlling crch Fitting
coef.crch

Methods for CRCH Objects
cnorm

The Censored Normal Distribution
crch

Censored Regression with Conditional Heteroscedasticy
coef.crch.boost

Methods for boosted CRCH Objects