plot.rq.process

Function to plot quantile regression process.

hplot

plot.rq

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

plot.rq function

<dl> <dt>x</dt>
<dd>an object produced by rq() fitting</dd> <dt>nrow</dt>
<dd>rows in mfrow</dd> <dt>ncol</dt>
<dd>columns in mfrow</dd> <dt>...</dt>
<dd>optional arguments to plot</dd></dl>

Arguments

Author

plot the coordinates of the quantile regression process — plot.rq

<dl>

 <dt>x</dt>
<dd>an object produced by rq() fitting</dd>

 <dt>nrow</dt>
<dd>rows in mfrow</dd>

 <dt>ncol</dt>
<dd>columns in mfrow</dd>

 <dt>...</dt>
<dd>optional arguments to plot</dd>

</dl>

plot the coordinates of the quantile regression process

plot.rq: plot the coordinates of the quantile regression process

Description

Usage

Arguments

Author

See Also