Package: quantreg 5.99

quantreg: Quantile Regression

Estimation and inference methods for models for conditional quantile functions: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press, <doi:10.1017/CBO9780511754098> and Koenker, R. et al. (2017) Handbook of Quantile Regression, CRC Press, <doi:10.1201/9781315120256>.

Authors:Roger Koenker [cre, aut], Stephen Portnoy [ctb], Pin Tian Ng [ctb], Blaise Melly [ctb], Achim Zeileis [ctb], Philip Grosjean [ctb], Cleve Moler [ctb], Yousef Saad [ctb], Victor Chernozhukov [ctb], Ivan Fernandez-Val [ctb], Brian D Ripley [trl, ctb]

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quantreg/json (API)

# Install 'quantreg' in R:
install.packages('quantreg', repos = c('https://rkoenker.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • Bosco - Boscovich Data
  • CobarOre - Cobar Ore data
  • Mammals - Garland(1983) Data on Running Speed of Mammals
  • MelTemp - Daily maximum temperatures in Melbourne, Australia
  • Peirce - C.S. Peirce's Auditory Response Data
  • barro - Barro Data
  • engel - Engel Data
  • gasprice - Time Series of US Gasoline Prices
  • uis - UIS Drug Treatment study data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

13.43 score 17 stars 1.4k packages 2.3k scripts 421k downloads 154 mentions 154 exports 6 dependencies

Last updated 15 days agofrom:18dc7af3cd. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 22 2024
R-4.5-win-x86_64OKOct 22 2024
R-4.5-linux-x86_64OKOct 22 2024
R-4.4-win-x86_64OKOct 22 2024
R-4.4-mac-x86_64OKOct 22 2024
R-4.4-mac-aarch64OKOct 22 2024
R-4.3-win-x86_64OKOct 22 2024
R-4.3-mac-x86_64OKOct 22 2024
R-4.3-mac-aarch64OKOct 22 2024

Exports:AIC.nlrqAIC.rqAIC.rqsAIC.rqssakjanova.rqanova.rqlistanova.rqsbandwidth.rqboot.crqboot.rqboot.rq.mcmbboot.rq.pwxyboot.rq.pwyboot.rq.pxyboot.rq.spwyboot.rq.wxyboot.rq.xyChangeLogcoef.crqcoef.nlrqcomboscritvalcrqcrq.fit.pencrq.fit.porcrq.fit.por2crq.fit.powCurvdeviance.nlrqditherdynrqend.dynrqextractAIC.nlrqextractAIC.rqFAQfitted.nlrqfitted.rqssformula.nlrqformula.rqHillHill.fitindex.dynrqKhmaladzeTestkselectkuantilekuniqueLassoLambdaHatlatexlatex.summary.rqslatex.tablelatex.table.rqlm.fit.recursivelogLik.nlrqlogLik.rqlogLik.rqslogLik.rqsslprqMungenlrqnlrq.controlnlrqModelParetoTestPickandsPickands.fitplot.qss1plot.qss2plot.rq.processplot.rqsplot.rqssplot.summary.crqsplot.summary.rqsplot.summary.rqssplot.table.rqpredict.crqpredict.crqspredict.nlrqpredict.qss1predict.qss2predict.rqpredict.rq.processpredict.rqspredict.rqssprint.anova.rqprint.crqprint.dynrqprint.dynrqsprint.Hillprint.nlrqprint.Pickandsprint.rqprint.rqsprint.rqssprint.summary.crqprint.summary.crqsprint.summary.dynrqprint.summary.dynrqsprint.summary.Hillprint.summary.nlrqprint.summary.Pickandsprint.summary.rqprint.summary.rqsprint.summary.rqssq489qriskqssqss1qss2QTECoxqts1ranksrearrangeresid.rqssresiduals.nlrqrqrq.fitrq.fit.brrq.fit.conquerrq.fit.fnbrq.fit.fncrq.fit.hoggrq.fit.lassorq.fit.pfnrq.fit.pfnbrq.fit.pprorq.fit.qfnbrq.fit.scadrq.fit.sfnrq.fit.sfncrq.test.anowarrq.test.rankrq.wfitrqProcessrqs.fitrqssrqss.fitsfn.controlsfnMessagesriskstart.dynrqsummary.crqsummary.crqssummary.dynrqssummary.Hillsummary.nlrqsummary.Pickandssummary.rqsummary.rqssummary.rqsstable.rqtau.nlrqtriogram.fidelitytriogram.penaltyuntangle.specials

Dependencies:latticeMASSMatrixMatrixModelsSparseMsurvival

quantreg: crq

Rendered fromcrq.pdf.asisusingR.rsp::asison Oct 22 2024.

Last update: 2019-07-15
Started: 2019-07-15

quantreg: rq

Rendered fromrq.pdf.asisusingR.rsp::asison Oct 22 2024.

Last update: 2019-07-15
Started: 2019-07-15

Readme and manuals

Help Manual

Help pageTopics
Density Estimation using Adaptive Kernel methodakj
Anova function for quantile regression fitsanova.rq anova.rqlist anova.rqs print.anova.rq rq.test.anowar rq.test.rank
bandwidth selection for rq functionsbandwidth.rq
Barro Databarro
Bootstrapping Censored Quantile Regressionboot.crq
Bootstrapping Quantile Regressionboot.rq boot.rq.mcmb boot.rq.pwy boot.rq.spwy boot.rq.wxy boot.rq.xy
Preprocessing weighted bootstrap methodboot.rq.pwxy
Preprocessing bootstrap methodboot.rq.pxy
Boscovich DataBosco
Cobar Ore dataCobarOre
Ordered Combinationscombos
Hotelling Critical Valuescritval
Functions to fit censored quantile regression modelscoef.crq crq crq.fit.pen crq.fit.por crq.fit.por2 crq.fit.pow Curv predict.crq predict.crqs print.crq
Function to randomly perturb a vectordither
Dynamic Linear Quantile Regressiondynrq end.dynrq index.dynrq print.dynrq print.dynrqs print.summary.dynrq print.summary.dynrqs start.dynrq summary.dynrq summary.dynrqs time.dynrq
Engel Dataengel
FAQ and ChangeLog of a packageChangeLog FAQ
Time Series of US Gasoline Pricesgasprice
Tests of Location and Location Scale Shift Hypotheses for Linear ModelsKhmaladzeTest
Quicker Sample Quantileskselect kuantile kunique
Lambda selection for QR lasso problemsLassoLambdaHat
Make a latex version of an R objectlatex
Make a latex table from a table of rq resultslatex.summary.rqs
Writes a latex formatted table to a filelatex.table
Recursive Least Squareslm.fit.recursive
locally polynomial quantile regressionlprq
Garland(1983) Data on Running Speed of MammalsMammals
Daily maximum temperatures in Melbourne, AustraliaMelTemp
Munge rqss formulaMunge
Function to compute nonlinear quantile regression estimatesAIC.nlrq coef.nlrq deviance.nlrq extractAIC.nlrq fitted.nlrq formula.nlrq logLik.nlrq nlrq nlrqModel predict.nlrq print.nlrq print.summary.nlrq summary.nlrq tau.nlrq
Set control parameters for nlrqnlrq.control
Estimation and Inference on the Pareto Tail Exponent for Linear ModelsHill Hill.fit ParetoTest Pickands Pickands.fit print.Hill print.Pickands print.summary.Hill print.summary.Pickands summary.Hill summary.Pickands
C.S. Peirce's Auditory Response DataPeirce
Plot a KhmaladzeTest objectplot.KhmaladzeTest
plot the coordinates of the quantile regression processplot.rq.process
Visualizing sequences of quantile regressionsplot.rqs
Plot Method for rqss Objectsplot.qss1 plot.qss2 plot.qts1 plot.rqss plot.summary.rqss
Visualizing sequences of quantile regression summariesplot.summary.rq plot.summary.rqs
Quantile Regression Predictionpredict.rq predict.rq.process predict.rqs
Predict from fitted nonparametric quantile regression smoothing spline modelspredict.qss1 predict.qss2 predict.rqss
Print a KhmaladzeTest objectprint.KhmaladzeTest
Print an rq objectprint.rq print.rqs
Print Quantile Regression Summary Objectprint.summary.rq print.summary.rqs
Even Quicker Sample Quantilesq489
Function to compute Choquet portfolio weightsqrisk
Additive Nonparametric Terms for rqss Fittingqss qss1 qss2 qts1 triogram.fidelity triogram.penalty
Function to obtain QTE from a Cox modelQTECox
Quantile Regression Ranksranks
Rearrangementrearrange
Return residuals of an nlrq objectresiduals.nlrq
Quantile Regressionrq
Function to choose method for Quantile Regressionrq.fit
Quantile Regression Fitting by Exterior Point Methodsrq.fit.br
Optional Fitting Method for Quantile Regressionrq.fit.conquer
Quantile Regression Fitting via Interior Point Methodsrq.fit.fnb
Quantile Regression Fitting via Interior Point Methodsrq.fit.fnc
weighted quantile regression fittingrq.fit.hogg
Lasso Penalized Quantile Regressionrq.fit.lasso
Preprocessing Algorithm for Quantile Regressionrq.fit.pfn
Quantile Regression Fitting via Interior Point Methodsrq.fit.pfnb
Preprocessing fitting method for QRrq.fit.ppro
Quantile Regression Fitting via Interior Point Methodsrq.fit.qfnb
SCADPenalized Quantile Regressionrq.fit.scad
Sparse Regression Quantile Fittingrq.fit.sfn sfnMessage
Sparse Constrained Regression Quantile Fittingrq.fit.sfnc
Linear Quantile Regression ObjectAIC.rq AIC.rqs extractAIC.rq formula.rq logLik.rq logLik.rqs rq.object
Linear Quantile Regression Process Objectrq.process.object
Function to choose method for Weighted Quantile Regressionrq.wfit
Compute Standardized Quantile Regression ProcessrqProcess
Function to fit multiple response quantile regression modelsrqs.fit
Additive Quantile Regression Smoothingrqss rqss.fit untangle.specials [.terms
RQSS Objects and Summarization ThereofAIC.rqss fitted.rqss logLik.rqss print.rqss resid.rqss rqss.object
Set Control Parameters for Sparse Fittingsfn.control
Markowitz (Mean-Variance) Portfolio Optimizationsrisk
Summary methods for Censored Quantile Regressionplot.summary.crqs print.summary.crq print.summary.crqs summary.crq summary.crqs
Summary methods for Quantile Regressionsummary.rcrqs summary.rq summary.rqs
Summary of rqss fitprint.summary.rqss summary.rqss
Table of Quantile Regression Resultslatex.table.rq plot.table.rq table.rq
UIS Drug Treatment study datauis