REEMtree.object {REEMtree} | R Documentation |
Object representing a fitted REEMtree
.
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 |
Rebecca Sela rsela@stern.nyu.edu
Sela, Rebecca J., and Simonoff, Jeffrey S., “RE-EM Trees: A New Data Mining Approach for Longitudinal Data”.
data(simpleREEMdata) REEMresult<-REEMtree(Y~D+t+X, data=simpleREEMdata, random=~1|ID)