lmrob.fit {robustbase}R Documentation

MM-type estimator for regression

Description

Compute MM-type estimators of regression: An S-estimator is used as starting value, and an M-estimator with fixed scale and redescending psi-function is used from there. Optionally a D-step (Design Adaptive Scale estimate) as well as a second M-step is calculated.

Usage

lmrob.fit(x, y, control)

Arguments

x

design matrix (n x p) typically including a column of 1s for the intercept.

y

numeric response vector (of length n).

control

A list of control parameters as returned by lmrob.control, used for both the initial S-estimate and the subsequent M- and D-estimates.

Details

This function is the basic fitting function for MM-type estimation, called by lmrob and typically not to be used on its own.

It calls lmrob.S(..) and uses it as initial estimator. Note that by default the inference used (covariance matrix) depends crucially on the S-estimator used, and hence it is currently no longer possible to specify the S-estimator at this level.

Value

A list with components

fitted.values X beta

, i.e. X %*% coefficients.

residuals

the raw residuals, y - fitted.values

weights

robustness weights derived from the final M-estimator residuals (even when not converged).

rank
degree.freedom

n - rank

coefficients

estimated regression coefficient vector

scale

the robustly estimated error standard deviation

cov

variance-covariance matrix of coefficients, if the RWLS iterations have converged

control
iter
converged

logical indicating if the RWLS iterations have converged.

init.S

the whole initial S-estimator result, including its own converged flag, see lmrob.S (only for MM-estimates).

init

A similar list that contains the results of intermediate estimates (not for MM-estimates).

Author(s)

Matias Salibian-Barrera, Martin Maechler and Manuel Koller

See Also

lmrob, lmrob..M..fit, lmrob..D..fit, lmrob.S


[Package robustbase version 0.8-0 Index]