residuals.nlrq

Set algorithmic parameters for nlrq (nonlinear quantile regression function)

models

regression

nonlinear

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

residuals.nlrq function

<dl> <dt>object</dt>
<dd>an `nlrq' object as returned by function `nlrq'</dd> <dt>type</dt>
<dd>the type of residuals to return: "response" is the distance
 between observed and predicted values; "rho" is the weighted distance used
 to calculate the objective function in the minimisation algorithm as 
 tau * pmax(resid, 0) + (1 - tau) * pmin(resid, 0), where resid are the
 simple residuals as above (with type="response").</dd> <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Return residuals of an nlrq object — residuals.nlrq

<dl>

 <dt>object</dt>
<dd>an `nlrq' object as returned by function `nlrq'</dd>

 <dt>type</dt>
<dd>the type of residuals to return: "response" is the distance
 between observed and predicted values; "rho" is the weighted distance used
 to calculate the objective function in the minimisation algorithm as 
 tau * pmax(resid, 0) + (1 - tau) * pmin(resid, 0), where resid are the
 simple residuals as above (with type="response").</dd>

 <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

Return residuals of an nlrq object

residuals.nlrq: Return residuals of an nlrq object

Description

Usage

Arguments

See Also