Package: Qtools 1.5.9

Qtools: Utilities for Quantiles

Functions for unconditional and conditional quantiles. These include methods for transformation-based quantile regression, quantile-based measures of location, scale and shape, methods for quantiles of discrete variables, quantile-based multiple imputation, restricted quantile regression, directional quantile classification, and quantile ratio regression. A vignette is given in Geraci (2016, The R Journal) <doi:10.32614/RJ-2016-037> and included in the package.

Authors:Marco Geraci [aut, cph, cre], Alessio Farcomeni [ctb], Cinzia Viroli [ctb]

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Qtools.pdf |Qtools.html✨
Qtools/json (API)
NEWS

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

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

131 exports 2.05 score 26 dependencies 2 dependents 6 mentions 32 scripts 1.3k downloads

Last updated 11 months agofrom:1cc1301473. Checks:OK: 7 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 11 2024
R-4.5-win-x86_64NOTESep 11 2024
R-4.5-linux-x86_64NOTESep 11 2024
R-4.4-win-x86_64OKSep 11 2024
R-4.4-mac-x86_64OKSep 11 2024
R-4.4-mac-aarch64OKSep 11 2024
R-4.3-win-x86_64OKSep 11 2024
R-4.3-mac-x86_64OKSep 11 2024
R-4.3-mac-aarch64OKSep 11 2024

Exports:addnoiseaobcboot.rqtboot.rrqC_midrqLossC_midrqLoss_aoC_midrqLoss_bcC_phifunC_projfunC_rcTestcloglogcmidecdfcmidecdf.fitcoef.midrqcoef.qrrcoef.rq.countscoef.rqtcoefficients.midrqcoefficients.qrrcoefficients.rq.countscoefficients.rqtconfint.midquantiled1aod1bcd1mcjId2aod2bcd2mcjIdqcdqc.fitdqcControlfastDoCallfitted.midrqfitted.rq.countsfitted.rqtGOFTestinvaoinvbcinvclogloginvlogitinvmapinvmcjIinvmcjIIinvpowerbaseKhmaladzeFormatKhmaladzeTablel1Losslogitmapmarefmaref.rq.countsmaref.rqtmcjImcjIImice.impute.rqmice.impute.rrqmidecdfmidq2qmidquantilemidrqmidrq.fitmidrqControlnl.fit.rqtnlControlnlLossnlrq1nlrq2normalizeplot.midecdfplot.midq2qplot.midquantileplot.qlsspowerbasepowrecbasepredict.midrqpredict.qlsspredict.qrrpredict.rq.countspredict.rqtpredict.rrqprint.cmidecdfprint.dqcprint.GOFTestprint.midecdfprint.midquantileprint.midrqprint.qlssprint.qrrprint.rq.countsprint.rqtprint.rrqprint.summary.midrqprint.summary.qrrprint.summary.rqtprint.summary.rrqqexactqlssqlss.defaultqlss.formulaqlss.numericqlssPredRqqlssPredRqtqprimeqrrrcLossrcrqrcTestresiduals.midrqresiduals.rq.countsresiduals.rqtrq.countsrrqrrq.fitrrq.wfitse_rqtsparsitysparsity.rqsparsity.rqssparsity.rqtsummary.midrqsummary.qrrsummary.rqtsummary.rrqswitch_checkterms2exprtsrqtsrq2vcov_conquervcov.midrqvcov.qrr

Dependencies:bootconquercubaturedrFormulaglmxgtoolsKernSmoothlatticelmtestMASSMatrixMatrixModelsmatrixStatsmvtnormnpnumDerivquadprogquantdrquantregRcppRcppArmadillosandwichSparseMsurvivalzoo

Qtools: A Collection of Models and Tools for Quantile Inference

Marco Geraci, University of South Carolina

Rendered fromQtools.Rmdusingknitr::rmarkdownon Sep 11 2024.

Last update: 2019-07-13
Started: 2019-07-04

Readme and manuals

Help Manual

Help pageTopics
Utilities for QuantiliesQtools-package
Transformationsao bc invao invbc invmcjI invmcjII mcjI mcjII
A-level Chemistry ScoresChemistry
Mid-distribution Functionscmidecdf cmidecdf.fit
Extract Coefficientscoef.midrq coefficients.midrq
Extract Coefficientscoef.qrr coefficients.qrr
Extract Coefficientscoef.rq.counts coefficients.rq.counts
Extract Coefficientscoef.rqt coefficients.rqt
Mid-distribution Functionsconfint.midquantile
Directional Quantile Classificationdqc dqc.fit
Control parameters for dqc estimationdqcControl
Esterase Essay Dataesterase
Extract Fitted Values from Mid-Quantile Transformation Modelsfitted.midrq
Extract Fitted Values from Quantile Regression Models for Countsfitted.rq.counts
Extract Fitted Values from Quantile Regression Transformation Modelsfitted.rqt
Goodness-of-Fit Tests for Quantile Regression ModelsGOFTest
Khmaladze TestKhmaladzeFormat
Labor Pain Datalabor
Marginal Effectsmaref maref.rq.counts maref.rqt
QR-based Multiple Imputationmice.impute.rq mice.impute.rrq
Recover Ordinary Conditional Quantiles from Conditional Mid-Quantilesmidq2q
Mid-distribution Functionsmidecdf midquantile
Mid-Quantile Regression for Discrete Responsesmidrq midrq.fit
Control parameters for midrq estimationmidrqControl
Control parameters for gradient search estimationnlControl
Growth curve data on an orthdontic measurementOrthodont
Plot Quantile Functionsplot.midq2q
Plot Mid-distribution Functionsplot.midecdf plot.midquantile
Quantile-based Summary Statistics for Location, Scale and Shapeplot.qlss
Predictions from Mid-Quantile Regression Modelspredict.midrq
Predictions from Conditional LSS Objectspredict.qlss
Predictions from Quantile Ratio Regression Modelspredict.qrr
Predictions from rq.counts Objectspredict.rq.counts
Predictions from Quantile Regression Transformation Modelspredict.rqt
Predictions from Restricted Quantile Regression Modelspredict.rrq
Print Mid-distribution Functionsprint.cmidecdf
Print Directional Quantile Classification Objectsprint.dqc
Print Goodness-of-Fit Test for Quantile Regression Modelsprint.GOFTest
Print Mid-distribution Functionsprint.midecdf print.midquantile
Print Mid-Quantile Modelsprint.midrq print.summary.midrq
Print Quantile-based Summary Statistics for Location, Scale and Shapeprint.qlss
Print Quantile Ratio Regression Modelsprint.qrr print.summary.qrr
Print rq.countsprint.rq.counts
Print Transformation Modelsprint.rqt print.summary.rqt
Print Restricted Quantile Regression Modelsprint.rrq print.summary.rrq
Exact Confidence Intervals for Quantilesqexact
Quantile-based Summary Statistics for Location, Scale and Shapeqlss qlss.default qlss.formula qlss.numeric
Quantile Ratio Regressionqrr
Residuals from a midrq Objectsresiduals.midrq
Residuals from an rq.counts Objectresiduals.rq.counts
Residuals from an rqt Objectsresiduals.rqt
Quantile Regression for Countsrq.counts
Restricted Regression Quantilesrrq rrq.fit rrq.wfit
Sparsity Estimationsparsity sparsity.rq sparsity.rqs sparsity.rqt
Summary for Mid-Quantile Regression Modelssummary.midrq
Summary for Quantile Ratio Regression Modelssummary.qrr
Summary for Quantile Regression Tranformation Modelssummary.rqt
Summary for Restricted Quantile Regression Modelssummary.rrq
Quantile Regression Transformation Modelsnlrq1 nlrq2 rcrq tsrq tsrq2
Variance-Covariance Matrix for a Fitted Mid-Quantile Regression Model Objectvcov.midrq
Variance-Covariance Matrix for a Fitted Quantile Ratio Regression Model Objectvcov.qrr