REEMtree (version 0.90.3)

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

Description

Object representing a fitted REEMtree.

Arguments

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

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

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

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