Function used to set several parameters to control the selection of the optimal cut points in a logistic regression model
controlcatpredi(min.p.cat = 1, grid = 100, B = 50, eps=0.001,
b.method = c("ncoutcome", "coutcome"), print.gen = 0)A list with components for each of the possible arguments.
Set the minimun number of individuals in each category
Grid size for the AddFor and BackAddFor algorithms
Number of bootstrap replicates for the AUC bias correction procedure
An argument for the BackAddFor algorithm, indicating whether the improvement between iterations is considered significant
Allows to specify whether the bootstrap resampling should be done considering or not the outcome variable. The option "ncoutcome" indicates that the data is resampled without taking into account the response variable, while "coutcome" indicates that the data is resampled in regard to the response variable
corresponds to the argument print.level of the genoud function of the package rgenoud.
Irantzu Barrio, Maria Xose Rodriguez-Alvarez, Inmaculada Arostegui, Javier Roca-Pardinas and Xabier Amutxastegi.
Mebane Jr, W. R., & Sekhon, J. S. (2011). Genetic optimization using derivatives: the rgenoud package for R. Journal of Statistical Software 4211, 1-26.
See Also as catpredi.