boot.rq.pxy

Bootstrap method exploiting preprocessing strategy to reduce 
 computation time for large problem.

bootstrap

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

boot.rq.pxy function

<dl> <dt>x</dt>
<dd>Design matrix</dd> <dt>y</dt>
<dd>response vector</dd> <dt>s</dt>
<dd>matrix of multinomial draws for xy bootstrap</dd> <dt>tau</dt>
<dd>quantile of interest</dd> <dt>coef</dt>
<dd>point estimate of fitted object</dd> <dt>method</dt>
<dd>fitting method for bootstrap</dd> <dt>Mm.factor</dt>
<dd>constant to determine initial sample size</dd></dl>

Arguments

Author

Preprocessing bootstrap method — boot.rq.pxy

<dl>

 <dt>x</dt>
<dd>Design matrix</dd>

 <dt>y</dt>
<dd>response vector</dd>

 <dt>s</dt>
<dd>matrix of multinomial draws for xy bootstrap</dd>

 <dt>tau</dt>
<dd>quantile of interest</dd>

 <dt>coef</dt>
<dd>point estimate of fitted object</dd>

 <dt>method</dt>
<dd>fitting method for bootstrap</dd>

 <dt>Mm.factor</dt>
<dd>constant to determine initial sample size</dd>

</dl>

Preprocessing bootstrap method

boot.rq.pxy: Preprocessing bootstrap method

Description

Usage

Value

Arguments

Author

Details

References

See Also