residuals.lad

Computes raw or randomized quantile residual for least absolute regression.

models

L1 estimation for linear regression using Barrodale and Roberts' method
<doi:10.1145/355616.361024> and the EM algorithm <doi:10.1023/A:1020759012226>.
Estimation of mean and covariance matrix using the multivariate Laplace distribution,
density, distribution function, quantile function and random number generation
for univariate and multivariate Laplace distribution <doi:10.1080/03610929808832115>.
Implementation of Naik and Plungpongpun <doi:10.1007/0-8176-4487-3_7> for the
Generalized spatial median estimator is included.

Felipe Osorio

L1pack

Routines for L1 Estimation

Tymoteusz Wolodzko

residuals.lad function

<dl> <dt>object</dt>
<dd>a fitted model object.</dd> <dt>type</dt>
<dd>a character string indicating the <code>type</code> of residual. 
 Available options are <code>"working"</code>, <code>"response"</code> for raw residuals, 
 and <code>"quantile"</code> for quantile residuals, the latter being standardized 
 residuals.</dd> <dt>...</dt>
<dd>additional argument(s) for related methods.</dd></dl>

Arguments

Residuals for LAD regression — residuals.lad

<dl>

 <dt>object</dt>
<dd>a fitted model object.</dd>

 <dt>type</dt>
<dd>a character string indicating the <code>type</code> of residual. 
 Available options are <code>"working"</code>, <code>"response"</code> for raw residuals, 
 and <code>"quantile"</code> for quantile residuals, the latter being standardized 
 residuals.</dd>

 <dt>...</dt>
<dd>additional argument(s) for related methods.</dd>

</dl>

residuals.lad: Residuals for LAD regression

Description

Usage

Value

Arguments

References

Examples