eval.logreg: Evaluate a Logic Regression tree

Description

This function evaluates a logic tree, typically a part of an object generated by logreg.

Usage

eval.logreg(ltree, data)

Arguments

ltree

an object of class logregmodel or an object of class logregtree. Typically this object will be part of the result of an object of class logreg, generated with select = 1 (single model fit), select = 2 (multiple model fit), or select = 6 (greedy stepwise fit).

data

a data frame on which the logic tree is to be evaluated. data should be binary, and have the same number of columns as the bin component of the original logreg fit.

Value

A binary vector with length equal to the number of rows of data; a 1 corresponds to cases for which ltree was TRUE and a 0 corresponds to cases for which ltree was FALSE if ltree was an object of class logregtree or the trees component of such an object. Otherwise a matrix with one column for each tree in ltree.

References

Ruczinski I, Kooperberg C, LeBlanc ML (2003). Logic Regression, Journal of Computational and Graphical Statistics, 12, 475-511.

Ruczinski I, Kooperberg C, LeBlanc ML (2002). Logic Regression - methods and software. Proceedings of the MSRI workshop on Nonlinear Estimation and Classification (Eds: D. Denison, M. Hansen, C. Holmes, B. Mallick, B. Yu), Springer: New York, 333-344.

Examples

Run this code

# NOT RUN {
data(logreg.savefit1)
# myanneal <- logreg.anneal.control(start = -1, end = -4, iter = 25000, update = 1000)
# logreg.savefit1 <- logreg(resp = logreg.testdat[,1], bin=logreg.testdat[, 2:21], 
#                type = 2, select = 1, ntrees = 2, anneal.control = myanneal)
tree1 <- eval.logreg(logreg.savefit1$model$trees[[1]], logreg.savefit1$binary)
tree2 <- eval.logreg(logreg.savefit1$model$trees[[2]], logreg.savefit1$binary)
alltrees <- eval.logreg(logreg.savefit1$model, logreg.savefit1$binary)
# }

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