rqs.fit

Function intended for multiple response quantile regression
called from <code>boot.rq</code> for wild bootstrap option.

 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>.

Roger Koenker

quantreg

Quantile Regression

Stephen Portnoy

Blaise Melly

Achim Zeileis

Philip Grosjean

Cleve Moler

Yousef Saad

Victor Chernozhukov

Ivan Fernandez-Val

Martin Maechler

rqs.fit function

<dl><dt>x</dt>
<dd>the design matrix an n by p matrix.</dd><dt>y</dt>
<dd>the response variable as a n by m matrix</dd><dt>tau</dt>
<dd>the quantile desired, if tau lies outside (0,1)</dd><dt>tol</dt>
<dd>tolerance parameter for Barrodale and Roberts exterior point method.</dd></dl>

Arguments

Function to fit multiple response quantile regression models — rqs.fit

<dl>

<dt>x</dt>
<dd>the design matrix an n by p matrix.</dd>

<dt>y</dt>
<dd>the response variable as a n by m matrix</dd>

<dt>tau</dt>
<dd>the quantile desired, if tau lies outside (0,1)</dd>

<dt>tol</dt>
<dd>tolerance parameter for Barrodale and Roberts exterior point method.</dd>

</dl>

Function to fit multiple response quantile regression models

rqs.fit: Function to fit multiple response quantile regression models

Description

Usage

Arguments

See Also