robustbase (version 0.5-0-1)

summary.lmrob: Summary Method for "lmrob" Objects

Description

Summary method for Robject of class "lmrob" and print method for the summary object. Further, methods fitted(), residuals() or weights() work (via the default methods), and predict(), vcov(), model.matrix() have explicitly defined lmrob methods.

Usage

## S3 method for class 'lmrob':
summary(object, correlation = FALSE,
        symbolic.cor = FALSE, \dots)
## S3 method for class 'summary.lmrob':
print(x, digits = max(3, getOption("digits") - 3),
      symbolic.cor= x$symbolic.cor,
      signif.stars = getOption("show.signif.stars"), ...)

## S3 method for class 'lmrob':
vcov(object, \dots)
## S3 method for class 'lmrob':
model.matrix(object, \dots)

## S3 method for class 'lmrob':
predict(object, newdata = NULL, scale = NULL, \dots)

Arguments

object

an Robject of class lmrob, typically created by lmrob.

correlation

logical variable indicating whether to compute the correlation matrix of the estimated coefficients.

symbolic.cor

logical indicating whether to use symbols to display the above correlation matrix.

x

an Robject of class summary.lmrob, typically resulting from summary(lmrob(..),..).

digits

number of digits for printing, see digits in options.

signif.stars

logical variable indicating whether to use stars to display different levels of significance in the individual t-tests.

newdata

data.frame with new data values at which prediction should be done; see predict.

scale

scale (estimate) to be used; see predict.lm.

...

potentially more arguments passed to methods.

See Also

lmrob, summary.lm, print, summary.

Examples

mod1 <- lmrob(stack.loss ~ ., data = stackloss)
sa <- summary(mod1)  # calls summary.lmrob(....)
sa                   # dispatches to call print.summary.lmrob(....)

## correlation between estimated coefficients:
cov2cor(vcov(mod1))

cbind(fit = fitted(mod1), resid = residuals(mod1),
      wgts= weights(mod1),
      predict(mod1, interval="prediction"))

data(heart)
sm2 <- summary( m2 <- lmrob(clength ~ ., data = heart) )
sm2