| summary.lmrob {robustbase} | R Documentation |
Summary method for R object 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.
## S3 method for class 'lmrob':
summary(object, correlation = FALSE,
symbolic.cor = FALSE, ...)
## 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, ...)
## S3 method for class 'lmrob':
model.matrix(object, ...)
## S3 method for class 'lmrob':
predict(object, newdata = NULL, scale = NULL, ...)
object |
an R object 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 R object 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. |
lmrob, summary.lm,
print, summary.
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