serp.control | R Documentation |
Default control parameters for 'serp' fit. User-supplied control parameters could be specified in the main function.
serp.control( maxits = 5e01, eps = 1e-07, maxpen = 1e07, trace = 0L, maxAdjIter = 5e0, max.half.iter = 1e01, relTol = 1e-03, nrFold = 5e0, cv.seed = 1e01, grid.length = 5e01, misclass.thresh = 5e-01, minP = .Machine$double.eps, ...)
maxits |
the maximum number of Newton's iterations. Default to 100. |
eps |
threshold value during optimization at which the iteration routine terminates. In other words, when the reported change in the log-likelihood goes below this threshold, convergence is achieved. |
maxpen |
the upper end point of the interval from zero to be searched for a tuning parameter. |
trace |
prints the Newton's fitting process at each iteration step.If 0 (default) no information is printed, if 1, 2 or 3 different shades of information are printed. |
maxAdjIter |
the maximum allowable number of Newton step adjustment to forestall an early optimization failure. Defaults to 5. |
max.half.iter |
the maximum number of iteration step-halfings. Defaults to 10. |
relTol |
relative convergence tolerance, defaults to 1e-03. checks relative changes in the parameter estimates between Newton iterations. |
nrFold |
the number of k-fold cross validation for the CV tuning method. Default to k = 5. |
cv.seed |
single numeric value to change the random seed in CV tuning. |
grid.length |
the length of the discrete lambda grid for the penalty method. |
misclass.thresh |
to reset the classification threshold in
|
minP |
A near zero minimum value the fitted probabilities are allowed to get during iteration to prevent numerical instability . |
... |
additional arguments. |
a list of control parameters.
serp
library(serp) serp(rating ~ contact, slope = "parallel", link = "logit", control = list(maxits = 2e01, eps=1e-05, trace = 2), data = wine)
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