Package: crch 1.2-1
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:
crch_1.2-1.tar.gz
crch_1.2-1.zip(r-4.5)crch_1.2-1.zip(r-4.4)crch_1.2-1.zip(r-4.3)
crch_1.2-1.tgz(r-4.4-x86_64)crch_1.2-1.tgz(r-4.4-arm64)crch_1.2-1.tgz(r-4.3-x86_64)crch_1.2-1.tgz(r-4.3-arm64)
crch_1.2-1.tar.gz(r-4.5-noble)crch_1.2-1.tar.gz(r-4.4-noble)
crch_1.2-1.tgz(r-4.4-emscripten)crch_1.2-1.tgz(r-4.3-emscripten)
crch.pdf |crch.html✨
crch/json (API)
NEWS
# Install 'crch' in R: |
install.packages('crch', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/topmodels
- RainIbk - Precipitation Observations and Forecasts for Innsbruck
Last updated 15 days agofrom:81645b17c5. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 21 2024 |
R-4.5-win-x86_64 | OK | Oct 21 2024 |
R-4.5-linux-x86_64 | OK | Oct 21 2024 |
R-4.4-win-x86_64 | OK | Oct 21 2024 |
R-4.4-mac-x86_64 | OK | Oct 21 2024 |
R-4.4-mac-aarch64 | OK | Oct 21 2024 |
R-4.3-win-x86_64 | OK | Oct 21 2024 |
R-4.3-mac-x86_64 | OK | Oct 21 2024 |
R-4.3-mac-aarch64 | OK | Oct 21 2024 |
Exports:CensoredLogisticCensoredNormalCensoredStudentsTcrchcrch.boostcrch.boost.fitcrch.controlcrch.fitcrch.stabseldclogisdcnormdctdtlogisdtnormdttgetSummary.crchhxlrhxlr.controlpclogispcnormpctptlogisptnormpttqclogisqcnormqctqtlogisqtnormqttrclogisrcnormrctrtlogisrtnormrtttrchTruncatedLogisticTruncatedNormalTruncatedStudentsT
Dependencies:evaluateFormulahighrknitrlatticeMASSMatrixnlmenumDerivordinalRcppRcppArmadillosandwichscoringRulesucminfxfunyamlzoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create a Censored Logistic Distribution | cdf.CensoredLogistic CensoredLogistic crps.CensoredLogistic is_continuous.CensoredLogistic is_discrete.CensoredLogistic kurtosis.CensoredLogistic log_pdf.CensoredLogistic mean.CensoredLogistic pdf.CensoredLogistic quantile.CensoredLogistic random.CensoredLogistic skewness.CensoredLogistic support.CensoredLogistic variance.CensoredLogistic |
Create a Censored Normal Distribution | cdf.CensoredNormal CensoredNormal crps.CensoredNormal is_continuous.CensoredNormal is_discrete.CensoredNormal kurtosis.CensoredNormal log_pdf.CensoredNormal mean.CensoredNormal pdf.CensoredNormal quantile.CensoredNormal random.CensoredNormal skewness.CensoredNormal support.CensoredNormal variance.CensoredNormal |
Create a Censored Student's T Distribution | cdf.CensoredStudentsT CensoredStudentsT crps.CensoredStudentsT is_continuous.CensoredStudentsT is_discrete.CensoredStudentsT kurtosis.CensoredStudentsT log_pdf.CensoredStudentsT mean.CensoredStudentsT pdf.CensoredStudentsT quantile.CensoredStudentsT random.CensoredStudentsT skewness.CensoredStudentsT support.CensoredStudentsT variance.CensoredStudentsT |
The Censored Logistic Distribution | dclogis pclogis qclogis rclogis |
The Censored Normal Distribution | dcnorm pcnorm qcnorm rcnorm |
Methods for Fitted crch Models | coef.crch crps.crch estfun.crch fitted.crch getSummary.crch logLik.crch model.frame.crch model.matrix.crch print.crch print.summary.crch residuals.crch summary.crch terms.crch vcov.crch |
Methods for Boosted crch Models | coef.crch.boost logLik.crch.boost print.crch.boost print.summary.crch.boost summary.crch.boost |
Methods for Fitted hxlr Models | coef.hxlr logLik.hxlr print.hxlr print.summary.hxlr summary.hxlr terms.hxlr vcov.hxlr |
Censored and Truncated Regression with Conditional Heteroscedasticy | crch crch.fit trch |
Auxiliary Functions for Boosting crch Models | crch.boost crch.boost.fit |
Control Options for crch Models | crch.control |
Auxiliary Functions for Stability Selection Using Boosting | crch.stabsel |
The Censored Student-t Distribution | dct pct qct rct |
Heteroscedastic Extended Logistic Regression | hxlr |
Control Options for hxlr Models | hxlr.control |
Visualizing Coefficient Paths for Boosted crch Models | plot.crch.boost |
Predictions for Fitted crch Models | predict.crch prodist.crch |
Predictions for Boosted crch Models | predict.crch.boost |
Predictions for Fitted hxlr Models | fitted.hxlr predict.hxlr |
Precipitation Observations and Forecasts for Innsbruck | RainIbk |
The Truncated Logistic Distribution | dtlogis ptlogis qtlogis rtlogis |
The Truncated Normal Distribution | dtnorm ptnorm qtnorm rtnorm |
Create a Truncated Logistic Distribution | cdf.TruncatedLogistic crps.TruncatedLogistic is_continuous.TruncatedLogistic is_discrete.TruncatedLogistic kurtosis.TruncatedLogistic log_pdf.TruncatedLogistic mean.TruncatedLogistic pdf.TruncatedLogistic quantile.TruncatedLogistic random.TruncatedLogistic skewness.TruncatedLogistic support.TruncatedLogistic TruncatedLogistic variance.TruncatedLogistic |
Create a Truncated Normal Distribution | cdf.TruncatedNormal crps.TruncatedNormal is_continuous.TruncatedNormal is_discrete.TruncatedNormal kurtosis.TruncatedNormal log_pdf.TruncatedNormal mean.TruncatedNormal pdf.TruncatedNormal quantile.TruncatedNormal random.TruncatedNormal skewness.TruncatedNormal support.TruncatedNormal TruncatedNormal variance.TruncatedNormal |
Create a Truncated Student's T Distribution | cdf.TruncatedStudentsT crps.TruncatedStudentsT is_continuous.TruncatedStudentsT is_discrete.TruncatedStudentsT kurtosis.TruncatedStudentsT log_pdf.TruncatedStudentsT mean.TruncatedStudentsT pdf.TruncatedStudentsT quantile.TruncatedStudentsT random.TruncatedStudentsT skewness.TruncatedStudentsT support.TruncatedStudentsT TruncatedStudentsT variance.TruncatedStudentsT |
The Truncated Student-t Distribution | dtt ptt qtt rtt |