disttree: Distributional Regression Tree

In disttree: Trees and Forests for Distributional Regression

Description

Trees based on maximum-likelihood estimation of parameters for specified distribution families, for example from the GAMLSS family (for generalized additive models for location, scale, and shape).

Usage

disttree(formula, data, subset, na.action = na.pass, weights, offset,
           cluster, family = NO(), control = disttree_control(...), 
           converged = NULL, scores = NULL, doFit = TRUE, ...)

Arguments

formula	a symbolic description of the model to be fit. This should be of type y ~ x1 + x2 where y should be the response variable and x1 and x2 are used as partitioning variables.
data	an optional data frame containing the variables in the model.
subset	an optional vector specifying a subset of observations to be used in the fitting process.
na.action	a function which indicates what should happen when the data contain missing value.
weights	optional numeric vector of case weights.
offset	an optional vector of offset values.
cluster	an optional factor indicating independent clusters. Highly experimental, use at your own risk.
family	specification of the response distribution. Either a gamlss.family object, a list generating function or a family list.
control	control arguments passed to extree_fit via disttree_control.

converged	an optional function for checking user-defined criteria before splits are implemented.
scores	an optional named list of scores to be attached to ordered factors.
doFit	a logical indicating if the tree shall be grown (TRUE) or not (FALSE).

...	arguments to be used to form the default control argument if it is not supplied directly.

Details

Distributional regression trees are an application of model-based recursive partitioning and unbiased recursive partitioning (implemented in extree_fit) to parametric model fits based on the GAMLSS family of distributions.

Value

An object of S3 class disttree inheriting from class modelparty.

See Also

mob, ctree, extree_fit, distfit

Examples

tr <- disttree(dist ~ speed, data = cars)
print(tr)

plot(tr)
plot(as.constparty(tr))

disttree documentation built on Aug. 14, 2019, 3 a.m.