htt.object {HTT}

Hypothesis Testing Tree Object

Description

A class for representing hypothesis testing tree.

Value

frame

a dataframe about the split information. It contains following information:

node: the node numbers in a split order.

parent: the parent node number.

leftChild: the left daughter node number, NA represents leaf.

rightChild: the right daughter node number, NA represents leaf.

statistic: the maximum test statistic of all possible splits within the node.

split: the rule of the split. It is numeric for continuous covariate split, it is a character for non-numeric covariate split, the levels of two child nodes are stored in two braces.

pval: approximate p-values estimated from permutation test.

isleaf: 1 denotes terminal node and 0 denotes internal node.

n: the number of observations reaching the node.

var: the names of the variables used in the split at each node (leaf nodes are denoted by the label "<leaf>").

yval: the fitted value of the response at the node, if the dimension of response is larger than 1, it will presents as yval1, yval2, ... .

prob: the probability of each class at the node, only visible for classification tree.

where

an integer vector of the same length as the number of observations in the root node, containing the row number of frame corresponding to the leaf node that each observation falls into.

method

the method used to grow the hypothesis testing tree, "regression" or "classification".

control

a list of options that control the HTT algorithm. See htt_control.

X

a copy of the input X in a dataframe format.

var.type

a vector recording for each variables, 0 represents continuous, 1 represents ordinal and 2 represents nominal variables.

See Also

HTT, plot.htt, print.htt, predict.htt