Usage
bst_control(mstop = 50, nu = 0.1, twinboost = FALSE,
f.init = NULL, xselect.init = NULL, center = FALSE, trace = FALSE,
numsample = 50, df=4)
Arguments
mstop
an integer giving the number of boosting iterations.
nu
a small number (between 0 and 1) defining the step size or shrinkage parameter.
twinboost
a logical value: TRUE for twin boosting.
f.init
the estimate from the first round of twin boosting. Only useful when twinboost=TRUE.
xselect.init
the variable selected from the first round of twin boosting. Only useful when twinboost=TRUE.
center
a logical value: TRUE to center covariates with mean.
trace
a logical value for printout of more details of information during
the fitting process.
numsample
number of random sample variable selected in the first round of twin boosting. This is potentially useful in the future implementation.
df
degree of freedom used in smoothing splines.