smooth_tree: Estimate BooST

In gabrielrvsc/BooST: Boosting Smooth Trees (BooST)

Description

Estimates Boosting of Smooth Trees (BooST)

Usage

smooth_tree(
  x,
  y,
  p = 1,
  d_max = 4,
  gamma = seq(0.5, 5, 0.01),
  node_obs = nrow(x)/200,
  random = FALSE
)

Arguments

x	Design matrix with explanatory variables.
y	Response variable.
p	Proportion of variables tested in each node split (default 1).
d_max	Number of splits in each tree (default 4).
gamma	Transiction function intensity. Bigger numbers makes the transition less smoth. The default is a sequence of values (0.5:5) to be randomized in each new node. Multiple values may be supplied in a vector to increase the model randomness.
node_obs	Equivalent to the minimum number of observations in a termina node for a discrete tree.
random	If TRUE trees are grown randomly (default = FALSE)

Value

An object with S3 class "SmoothTree".

Model	A list with all trees.
fitted.values	Final model fitted values.
nvar	Number of variables in x.
varnames	colnames of x to be used in other functions.
call	The matched call.

References

blablabla

Examples

## == to be made == ##

gabrielrvsc/BooST documentation built on July 27, 2021, 3:08 p.m.