This function extracts the residuals from the LME object underlying the REEM tree. The residuals depend on the fixed effects (from the tree) plus the estimated contributions of the random effects to the fitted values at grouping levels less or equal to the level given.
1  residuals.REEMtree(object, level, type, asList, ...)

object 
an object of class 
level 
the level of random effects used in creating residuals. Level 0 is fixed effects only; levels increase with the grouping of random effects. Default is the highest level. 
type 
optional character string specifying the type of residuals to be used. If 
asList 
an optional logical value. If 
... 
some methods for this generic require additional arguments; none are used here. 
If the level is a single value, the result is a vector or list (depending on asList
) with the residuals. Otherwise, the result is a data frame with columns given by the residuals at different levels.
Rebecca Sela rsela@stern.nyu.edu
Sela, Rebecca J., and Simonoff, Jeffrey S., “REEM Trees: A Data Mining Approach for Longitudinal and Clustered Data”, Machine Learning (2011).
residuals
, REEMtree.object
1 2 3  data(simpleREEMdata)
REEMresult<REEMtree(Y~D+t+X, data=simpleREEMdata, random=~1ID)
residuals(REEMresult)

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