R: Extract the residual scale of a robust regression model

getScale {robustHD} | R Documentation

## Extract the residual scale of a robust regression model

### Description

Extract the robust scale estimate of the residuals from a robust regression model.

### Usage

    getScale(x, ...)

    ## S3 method for class 'seqModel'
    getScale(x, s = NA, ...)

    ## S3 method for class 'sparseLTS'
    getScale(x, s = NA, fit = c("reweighted", "raw", "both"), ...)

### Arguments

`x` | the model fit from which to extract the robust residual scale estimate.
`...` | additional arguments to be passed down to methods.
`s` | for the `"seqModel"` method, an integer vector giving the steps of the submodels for which to extract the robust residual scale estimate (the default is to use the optimal submodel). For the `"sparseLTS"` method, an integer vector giving the indices of the models from which to extract the robust residual scale estimate. If `fit` is `"both"`, this can be a list with two components, with the first component giving the indices of the reweighted fits and the second the indices of the raw fits. The default is to use the optimal model for each of the requested estimators. Note that the optimal models may not correspond to the same value of the penalty parameter for the reweighted and the raw estimator.
`fit` | a character string specifying from which fit to extract the robust residual scale estimate. Possible values are `"reweighted"` (the default) for the residual scale of the reweighted fit, `"raw"` for the residual scale of the raw fit, or `"both"` for the residual scale of both fits.

### Details

Methods are implemented for models of class `"lmrob"` (see `lmrob`), `"lts"` (see `ltsReg`), `"rlm"` (see `rlm`), `"seqModel"` (see `rlars`) and `"sparseLTS"` (see `sparseLTS`). The default method computes the MAD of the residuals.

### Value

A numeric vector or matrix giving the robust residual scale estimates for the requested model fits.

### Author(s)

Andreas Alfons

### See Also

`AIC`, `lmrob`, `ltsReg`, `rlm`, `rlars`, `sparseLTS`

### Examples

    data("coleman")
    fit <- lmrob(Y ~ ., data=coleman)
    getScale(fit)

[Package robustHD version 0.7.2 Index]