summary.lmRob: Summarizing Robust Linear Model Fits

In robust: Port of the S+ "Robust Library"

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

robust documentation built on May 2, 2019, 5:20 p.m.