Control Parameters for Bounded Influence Robust Regression

DESCRIPTION:

Allows the users to set values affecting the estimation procedure for robust regression in lmRobBI.

USAGE:

lmRobBI.control(efficiency=0.95, tuning.p=NULL, max.wt=150, max.rg=30,  
alg="W", tol=1e-05, tau=1e-11) 

OPTIONAL ARGUMENTS:

efficiency
the asymptotic efficiency of the bounded influence estimates.
tuning.p
a scalar which gives the value of the tuning constant for the psi-function of the corresponding generalized M-estimator. It is only used if method="mal".
max.wt
the maximum number of iterations to compute the optimal weights.
max.rg
the maximum number of iterations to compute the regression estimates.
alg
specifies the algorithm which will be used to compute the regression estimates. If alg="W", the conjugate gradient algorithm will be used; if alg="N", the Newton-Huber algorithm will be used.
tol
the relative tolerance in the iterative algorithms.
tau
the tolerance used for the determination of pseudo-rank.

VALUE:

a list containing the values used for each of the control parameters.

SEE ALSO:

.

EXAMPLES:

control.95 <- lmRobBI.control(efficiency=0.85)