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quantreg (version 5.73)

Quantile Regression

Description

Estimation and inference methods for models of conditional quantiles: 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.

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Version

Install

install.packages('quantreg')

Monthly Downloads

337,319

Version

5.73

License

GPL (>= 2)

Maintainer

Roger Koenker

Last Published

October 2nd, 2020

Functions in quantreg (5.73)

CobarOre

Cobar Ore data
Mammals

Garland(1983) Data on Running Speed of Mammals
akj

Density Estimation using Adaptive Kernel method
Peirce

C.S. Peirce's Auditory Response Data
Bosco

Boscovich Data
FAQ

FAQ and ChangeLog of a package
QTECox

Function to obtain QTE from a Cox model
KhmaladzeTest

Tests of Location and Location Scale Shift Hypotheses for Linear Models
anova.rq

Anova function for quantile regression fits
ParetoTest

Estimation and Inference on the Pareto Tail Exponent for Linear Models
dither

Function to randomly perturb a vector
boot.crq

Bootstrapping Censored Quantile Regression
latex

Make a latex version of an R object
kuantile

Quicker Sample Quantiles
critval

Hotelling Critical Values
boot.rq

Bootstrapping Quantile Regression
crq

Functions to fit censored quantile regression models
bandwidth.rq

bandwidth selection for rq functions
boot.rq.pxy

Preprocessing bootstrap method
plot.summary.rqs

Visualizing sequences of quantile regression summaries
engel

Engel Data
gasprice

Time Series of US Gasoline Prices
latex.summary.rqs

Make a latex table from a table of rq results
combos

Ordered Combinations
nlrq

Function to compute nonlinear quantile regression estimates
plot.rqs

Visualizing sequences of quantile regressions
dynrq

Dynamic Linear Quantile Regression
predict.rq

Quantile Regression Prediction
barro

Barro Data
nlrq.control

Set control parameters for nlrq
rq.fit.conquer

Optional Fitting Method for Quantile Regression
plot.rq

plot the coordinates of the quantile regression process
plot.KhmaladzeTest

Plot a KhmaladzeTest object
latex.table

Writes a latex formatted table to a file
plot.rqss

Plot Method for rqss Objects
qrisk

Function to compute Choquet portfolio weights
rq.fit.lasso

Lasso Penalized Quantile Regression
lm.fit.recursive

Recursive Least Squares
rq.fit.pfn

Preprocessing Algorithm for Quantile Regression
rq.fit.fnb

Quantile Regression Fitting via Interior Point Methods
rq.fit.fnc

Quantile Regression Fitting via Interior Point Methods
ranks

Quantile Regression Ranks
rq.fit.sfnc

Sparse Constrained Regression Quantile Fitting
qss

Additive Nonparametric Terms for rqss Fitting
rq.fit.sfn

Sparse Regression Quantile Fitting
predict.rqss

Predict from fitted nonparametric quantile regression smoothing spline models
rq.fit.hogg

weighted quantile regression fitting
rearrange

Rearrangement
rq.wfit

Function to choose method for Weighted Quantile Regression
lprq

locally polynomial quantile regression
rq.fit

Function to choose method for Quantile Regression
print.KhmaladzeTest

Print a KhmaladzeTest object
print.rq

Print an rq object
print.summary.rq

Print Quantile Regression Summary Object
rq.fit.br

Quantile Regression Fitting by Exterior Point Methods
rqProcess

Compute Standardized Quantile Regression Process
rq.fit.scad

SCADPenalized Quantile Regression
rq.fit.ppro

Preprocessing fitting method for QR
srisk

Markowitz (Mean-Variance) Portfolio Optimization
residuals.nlrq

Return residuals of an nlrq object
summary.rq

Summary methods for Quantile Regression
rqs.fit

Function to fit multiple response quantile regression models
summary.rqss

Summary of rqss fit
rqss

Additive Quantile Regression Smoothing
rq

Quantile Regression
summary.crq

Summary methods for Censored Quantile Regression
table.rq

Table of Quantile Regression Results
uis

UIS Drug Treatment study data
rq.process.object

Linear Quantile Regression Process Object
rq.object

Linear Quantile Regression Object
rqss.object

RQSS Objects and Summarization Thereof
sfn.control

Set Control Parameters for Sparse Fitting