roblm.control {roblm}R Documentation

Tuning parameters for roblm

Description

Tuning parameters for the MM-regression estimator and the associated S-estimator

Usage

roblm.control(seed = 99, Nres = 500, 
        tuning.chi = 1.54764, bb = 0.5, tuning.psi = 4.685061, 
        groups = 5, n.group = 400, k.fast.s = 1,
        max.it = 50,
        compute.rd = TRUE
        ) 

Arguments

Nres Number of re-sampling candidates to be used to find the initial S-estimator. This parameter is currently set to 500, which works well in most situations (see References below). User-choice capability will be added in future releases
seed Random seed for the re-samples used in obtaining candiates for the initial S-estimator.
tuning.chi Tuning constant for the S-estimator. The choice 1.54764 yields a 50% breakdown estimator.
bb Expected value under the normal model of the "chi" function with tuning constant equal to tuning.chi. This is used to compute the S-estimator
max.it Maximum number of IRWLS iterations
tuning.psi Tuning constant for the re-descending M-estimator. The choice 4.685061 yields an estimator with asymptotic efficiency of 95% for normal errors.
compute.rd If TRUE robust distances (based on the MCD robust covariance matrix) are computed for the robust diagnostic plots. This may take some time to finish, specially for large data sets.
groups This parameter is for the fast-S algorithm. Number of random subsets to use when the data set is large.
n.group This parameter is for the fast-S algorithm. Size of each of the groups above.
k.fast.s This parameter is for the fast-S algorithm. Number of local improvement steps for each re-sampling candidate.

Author(s)

Matias Salibian-Barrera

See Also

roblm


[Package roblm version 0.6 Index]