GPLTR (version 1.5)

nested.trees: compute the nested trees

Description

Compute a sequence of nested competing trees for the prunning step

Usage

nested.trees(xtree, xdata, Y.name, X.names, MaxTreeSize = NULL,
family = "binomial", verbose = TRUE)

Value

a list with 4 elements:

leaves

a list of leaves of the competing trees to consider for the optimal tree

null_deviance

the deviance of the null model (linear part of the glm)

deviances

a vector of deviances of the competing PLTR models

diff_deviances

a vector of the deviance differencies between the competing PLTR models and the null model

Arguments

xtree

a tree inheriting to the rpart method

xdata

the dataset used to build the tree

Y.name

the name of the dependent variable in the tree model

X.names

the names of independent variables considered as offset in the tree model

MaxTreeSize

The maximal size of the competing trees

family

the glm family considered depending on the type of the dependent variable.

verbose

Logical; TRUE for printing progress during the computation (helpful for debugging)

Author

Cyprien Mbogning and Wilson Toussile

Examples

if (FALSE) {
## load the data set

data(data_pltr)
args.rpart <- list(minbucket = 40, maxdepth = 10, cp = 0)
family <- "binomial"
Y.name <- "Y"
X.names <- "G1"
G.names <- paste("G", 2:15, sep="")

## build a maximal tree

fit_pltr <- pltr.glm(data_pltr, Y.name, X.names, G.names, args.rpart = args.rpart, 
                     family = family,iterMax = 5, iterMin = 3)
                     
## compute the competing trees

nested_trees <- nested.trees(fit_pltr$tree, data_pltr, Y.name, X.names, 
                            MaxTreeSize = 10, family = family)
}