R: Summarizing Robust Linear Model Fits

summary.lmRob {robust} | R Documentation

## Summarizing Robust Linear Model Fits

### Description

Compute a summary of the robustly fitted linear model.

### Usage

    ## S3 method for class 'lmRob'
    summary(object, correlation = FALSE, bootstrap.se = FALSE, ...)

### Arguments

`object` | an lmRob object.
`correlation` | a logical value. If `TRUE` then the correlation matrix of the coefficients is included in the summary.
`bootstrap.se` | a logical value. If `TRUE` then bootstrap standard error estimates are included in the summary.
`...` | additional arguments required by the generic `summary` function.

### Value

The summary is returned in a list of class summary.lmRob and contains the following components:

`sigma` | a single numeric value containing the residual scale estimate.
`df` | a numeric vector of length 3 containing integer values: the rank of the model matrix, the residual degrees of freedom, and the number of coefficients in the model.
`cov.unscaled` | the unscaled covariance matrix; i.e, the matrix that, when multiplied by the estimate of the error variance, yields the estimated covariance matrix for the coefficients.
`correlation` | the correlation coefficient matrix for the coefficients in the model.
`...` | the remaining components are the same as the corresponding components in an `lmRob` object. Use the `names` function to obtain a list of the components.

### Examples

    data(stack.dat)
    stack.rob <- lmRob(Loss ~ ., data = stack.dat)
    stack.sum <- summary(stack.rob)
    stack.sum
    stack.bse <- summary(stack.rob, bootstrap.se = TRUE)
    stack.bse

[Package robust version 0.6-0 Index]