Tuning parameters for lmrobM
This function sets tuning parameters for the M estimators of regression implemented
in lmrobM.
lmrobM.control(bb = 0.5, efficiency = 0.99, family = "opt", tuning.chi, tuning.psi, max.it = 100, rel.tol = 1e-07, mscale_tol = 1e-06, mscale_maxit = 50, trace.lev = 0)
bb |
tuning constant (between 0 and 1/2) for the M-scale used to compute the residual scale estimator. Defaults to 0.5. |
efficiency |
desired asymptotic efficiency of the final regression M-estimator. Defaults to 0.85. |
family |
string specifying the name of the family of loss function to be used (current valid options are "bisquare", "opt" and "mopt"). Incomplete entries will be matched to the current valid options. |
tuning.chi |
tuning constant for the function used to compute the M-scale
used for the residual scale estimator. If missing, it is computed inside |
tuning.psi |
tuning parameters for the regression M-estimator computed with a rho function
as specified with argument |
max.it |
maximum number of IRWLS iterations for the M-estimator |
rel.tol |
relative covergence tolerance for the IRWLS iterations for the M-estimator |
mscale_tol |
Convergence tolerance for the M-scale algorithm. See |
mscale_maxit |
Maximum number of iterations for the M-scale algorithm. See |
trace.lev |
positive values (increasingly) provide details on the progress of the M-algorithm |
A list with the necessary tuning parameters.
Matias Salibian-Barrera, matias@stat.ubc.ca
data(coleman, package='robustbase') m2 <- lmrobM(Y ~ ., data=coleman, control=lmrobM.control()) m2 summary(m2)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.