Package: Qtools 1.6.1

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]

Qtools_1.6.1.tar.gz
Qtools_1.6.1.zip(r-4.7)Qtools_1.6.1.zip(r-4.6)Qtools_1.6.1.zip(r-4.5)
Qtools_1.6.1.tgz(r-4.6-x86_64)Qtools_1.6.1.tgz(r-4.6-arm64)Qtools_1.6.1.tgz(r-4.5-x86_64)Qtools_1.6.1.tgz(r-4.5-arm64)
Qtools_1.6.1.tar.gz(r-4.7-arm64)Qtools_1.6.1.tar.gz(r-4.7-x86_64)Qtools_1.6.1.tar.gz(r-4.6-arm64)Qtools_1.6.1.tar.gz(r-4.6-x86_64)
Qtools_1.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
Qtools/json (API)
NEWS

# Install 'Qtools' in R:

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

Bug tracker:https://github.com/marco-geraci/qtools/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

Chemistry - A-level Chemistry Scores
esterase - Esterase Assay Data
fars - FARS Data
labor - Labor Pain Data
Orthodont - Growth curve data on an orthdontic measurement

On CRAN:

cpp

6.39 score 2 packages 45 scripts 534 downloads 6 mentions 138 exports 26 dependencies

Last updated from:6e802e40e3. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	164
linux-devel-x86_64	NOTE	183
source / vignettes	OK	227
linux-release-arm64	NOTE	167
linux-release-x86_64	NOTE	182
macos-release-arm64	NOTE	127
macos-release-x86_64	NOTE	302
macos-oldrel-arm64	NOTE	98
macos-oldrel-x86_64	NOTE	312
windows-devel	NOTE	160
windows-release	NOTE	155
windows-oldrel	NOTE	129
wasm-release	OK	121

Exports:addnoise ao bc boot.rqt boot.rrq C_midrqLoss C_midrqLoss_ao C_midrqLoss_bc C_phifun C_projfun C_rcTest cloglog cmidecdf cmidecdf.fit coef.midrq coef.qrr coef.rq.counts coef.rqt coefficients.midrq coefficients.qrr coefficients.rq.counts coefficients.rqt confint.midquantile d1ao d1bc d1mcjI d2ao d2bc d2mcjI dqc dqc.fit dqcControl fastDoCall fitted.midrq fitted.rq.counts fitted.rqt GOFTest invao invbc invcloglog invlogit invmap invmcjI invmcjII invpowerbase KhmaladzeFormat KhmaladzeTable l1Loss LOFTest logit map maref maref.rq.counts maref.rqt mcjI mcjII mice.impute.rq mice.impute.rrq midecdf midq2q midq2q.midquantile midq2q.midrq midquantile midrq midrq.fit midrqControl nl.fit.rqt nlControl nlLoss nlrq1 nlrq2 normalize plot.midecdf plot.midq2q plot.midquantile plot.qlss powerbase powrecbase predict.midrq predict.qlss predict.qrr predict.rq.counts predict.rqt predict.rrq print.cmidecdf print.dqc print.GOFTest print.LOFTest print.midecdf print.midquantile print.midrq print.qlss print.qrr print.rq.counts print.rqt print.rrq print.summary.midrq print.summary.qrr print.summary.rqt print.summary.rrq qexact qlss qlss.default qlss.formula qlss.numeric qlssPredRq qlssPredRqt qprime qr_var qrr qsmspline qtr_var rcLoss rcrq rcTest residuals.midrq residuals.rq.counts residuals.rqt rq.counts rrq rrq.fit rrq.wfit se_rqt sparsity sparsity.rq sparsity.rqs sparsity.rqt summary.midrq summary.qrr summary.rqt summary.rrq switch_check terms2expr tsrq tsrq2 vcov_conquer vcov.midrq vcov.qrr

Dependencies:boot conquer corpcor cubature Formula glmx gtools KernSmooth lattice lmtest MASS Matrix MatrixModels matrixStats mvtnorm np numDeriv quadprog quantdr quantreg Rcpp RcppArmadillo sandwich SparseM survival zoo

Qtools: A Collection of Models and Tools for Quantile Inference

Marco Geraci, University of South Carolina

Rendered fromQtools.Rmdusingknitr::rmarkdownon May 24 2026.

Last update: 2020-05-24
Started: 2019-07-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Utilities for Quantilies	Qtools-package
Transformations	ao bc invao invbc invmcjI invmcjII mcjI mcjII
A-level Chemistry Scores	Chemistry
Mid-distribution Functions	cmidecdf cmidecdf.fit
Extract Coefficients	coef.midrq coefficients.midrq
Extract Coefficients	coef.qrr coefficients.qrr
Extract Coefficients	coef.rq.counts coefficients.rq.counts
Extract Coefficients	coef.rqt coefficients.rqt
Mid-distribution Functions	confint.midquantile
Directional Quantile Classification	dqc dqc.fit
Control parameters for dqc estimation	dqcControl
Esterase Assay Data	esterase
FARS Data	fars
Extract Fitted Values from Mid-Quantile Transformation Models	fitted.midrq
Extract Fitted Values from Quantile Regression Models for Counts	fitted.rq.counts
Extract Fitted Values from Quantile Regression Transformation Models	fitted.rqt
Khmaladze Test	KhmaladzeFormat
Labor Pain Data	labor
Lack-of-Fit Tests for Quantile Regression Models	GOFTest LOFTest
Marginal Effects	maref maref.rq.counts maref.rqt
QR-based Multiple Imputation	mice.impute.rq mice.impute.rrq
Recover Ordinary Quantiles from Mid-Quantiles	midq2q midq2q.midquantile midq2q.midrq
Mid-distribution Functions	midecdf midquantile
Mid-Quantile Regression for Discrete Responses	midrq midrq.fit
Control parameters for midrq estimation	midrqControl
Control parameters for gradient search estimation	nlControl
Growth curve data on an orthdontic measurement	Orthodont
Plot Quantile Functions	plot.midq2q
Plot Mid-distribution Functions	plot.midecdf plot.midquantile
Quantile-based Summary Statistics for Location, Scale and Shape	plot.qlss
Predictions from Mid-Quantile Regression Models	predict.midrq
Predictions from Conditional LSS Objects	predict.qlss
Predictions from Quantile Ratio Regression Models	predict.qrr
Predictions from rq.counts Objects	predict.rq.counts
Predictions from Quantile Regression Transformation Models	predict.rqt
Predictions from Restricted Quantile Regression Models	predict.rrq
Print Mid-distribution Functions	print.cmidecdf
Print Directional Quantile Classification Objects	print.dqc
Print Lack-of-Fit Test for Quantile Regression Models	print.GOFTest print.LOFTest
Print Mid-distribution Functions	print.midecdf print.midquantile
Print Mid-Quantile Models	print.midrq print.summary.midrq
Print Quantile-based Summary Statistics for Location, Scale and Shape	print.qlss
Print Quantile Ratio Regression Models	print.qrr print.summary.qrr
Print rq.counts	print.rq.counts
Print Transformation Models	print.rqt print.summary.rqt
Print Restricted Quantile Regression Models	print.rrq print.summary.rrq
Exact Confidence Intervals for Quantiles	qexact
Quantile-based Summary Statistics for Location, Scale and Shape	qlss qlss.default qlss.formula qlss.numeric
Variance for Ratios of Quantiles and Tail means	qr_var qtr_var
Quantile Ratio Regression	qrr
Quantile Regression with Smoothing Splines	qsmspline
Residuals from a midrq Objects	residuals.midrq
Residuals from an rq.counts Object	residuals.rq.counts
Residuals from an rqt Objects	residuals.rqt
Quantile Regression for Counts	rq.counts
Restricted Regression Quantiles	rrq rrq.fit rrq.wfit
Sparsity Estimation	sparsity sparsity.rq sparsity.rqs sparsity.rqt
Summary for Mid-Quantile Regression Models	summary.midrq
Summary for Quantile Ratio Regression Models	summary.qrr
Summary for Quantile Regression Tranformation Models	summary.rqt
Summary for Restricted Quantile Regression Models	summary.rrq
Quantile Regression Transformation Models	nlrq1 nlrq2 rcrq tsrq tsrq2
Variance-Covariance Matrix for a Fitted Mid-Quantile Regression Model Object	vcov.midrq
Variance-Covariance Matrix for a Fitted Quantile Ratio Regression Model Object	vcov.qrr