REEMtree.object: Random Effects/Expectation Maximization (RE-EM) Tree Object

In REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data

Random Effects/Expectation Maximization (RE-EM) Tree Object

Description

Object representing a fitted REEMtree.

Value

Tree	Fitted rpart tree associated with the fitted RE-EM tree
EffectModel	fitted lme object associated with the fitted RE-EM tree
RandomEffects	vector of estimated random effects
BetweenMatrix	estimated variance of the random effects
ErrorVariance	estimated variance of the errors
data	the data frame used to estimate the RE-EM tree
logLik	log likelihood of the linear model for the random effects
IterationsUsed	number of iterations required to fit the REEMtree
Formula	formula used in fitting the REEMtree
Random	description of the random effects used in fitting the REEMtree
Groups	the vector of group identifiers used in estimation
Subset	the logical vector indicating the subset of the rows of data used in the fit
ErrorTolerance	the error tolerance used in estimation
correlation	the correlation structure used in fitting the linear model
residuals	estimated residuals
method	method (ML or REML) used in estimating the linear random effects model
lme.control	parameters used to control fitting the linear random effects mdoel
tree.control	parameters used to control fitting the regression tree

Author(s)

Rebecca Sela [e-mail]

References

Sela, Rebecca J., and Simonoff, Jeffrey S., “RE-EM Trees: A Data Mining Approach for Longitudinal and Clustered Data”, Machine Learning (2011).

See Also

rpart, nlme, REEMtree

Examples

data(simpleREEMdata)
REEMresult<-REEMtree(Y~D+t+X, data=simpleREEMdata, random=~1|ID)

REEMtree documentation built on Oct. 25, 2023, 1:08 a.m.