robust (version 0.3-0)

summary.lmRob: 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