rlm(formula, data, weights, subset, na.action, model=F, k=1.345, sw=1000, ...)
formula
|
a formula object, with the response on the left of a ~ operator,
and the terms, separated by + operators, on the right.
|
data
|
an optional data.frame in which to interpret the variables named in the
formula, or in the subset and the weights argument.
|
weights
| optional weights; if supplied, the algorithm fits to minimize the sum of the weights multiplied into the squared residuals. The weights must be strictly positive. |
subset
| optional expression saying that only a subset of the rows of the data should be used in the fit. |
na.action
|
a missing-data filter function, applied to the model.frame , after
any subset argument has been used.
|
model
|
flag to control what is returned. If this is TRUE , then the model frame
is returned. X and y are always returned.
|
k
| The control value for Winsorizing. The default gives 95% efficiency at the normal. |
sw
|
switch to Huber proposal 2 scale at iteration sw and beyond.
|
...
|
additional arguments for the fitting routines.
The most likely one is maxit , which sets the iteration limit, by default
20.
|
sw
iterations.
Generic functions such as print
and summary
have methods to
show the results of the fit.
rlm
representing the fit, inheriting from lm
.
This has all the components of an lm
object, plus k,
the scale s
and
conv
which is a vector monitoring the convergence.summary.rlm
data(phones) attach(phones) res <- rlm(calls ~ year) print(res) data(stack) rlm(stack.loss ~ stack.x)