serp.control  R Documentation 
Default control parameters for 'serp' fit. Usersupplied control parameters could be specified in the main function.
serp.control( maxits = 5e01, eps = 1e07, maxpen = 1e07, trace = 0L, maxAdjIter = 5e0, max.half.iter = 1e01, relTol = 1e03, nrFold = 5e0, cv.seed = 1e01, grid.length = 5e01, misclass.thresh = 5e01, 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 loglikelihood 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 stephalfings. Defaults to 10. 
relTol 
relative convergence tolerance, defaults to 1e03. checks relative changes in the parameter estimates between Newton iterations. 
nrFold 
the number of kfold 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=1e05, trace = 2), data = wine)
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