Extract the estimated random effects from a RE-EM tree

Description

This function extracts the estimated random effects from a fitted RE-EM tree.

Usage

ranef.REEMtree(object,...)

Arguments

Value

a vector containing the estimated random effects

Author(s)

Rebecca Sela rsela@stern.nyu.edu

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

random.effects, REEMtree.object

Examples

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

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(REEMtree)
Loading required package: nlme
Loading required package: rpart
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/REEMtree/ranef.REEMtree.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ranef.REEMtree
> ### Title: Extract the estimated random effects from a RE-EM tree
> ### Aliases: ranef.REEMtree
> ### Keywords: models
> 
> ### ** Examples
> 
> data(simpleREEMdata)
> REEMresult<-REEMtree(Y~D+t+X, data=simpleREEMdata, random=~1|ID)
> ranef(REEMresult)
   (Intercept)
1   0.32500089
2  -1.75073523
3  -1.14491317
4  -0.73369277
5   1.16140267
6   0.64948348
7  -1.80986881
8  -0.96309830
9   1.37102427
10  1.85634184
11  0.35248096
12 -0.13528313
13  1.72417909
14 -1.32663863
15 -1.12580990
16 -0.83848132
17  0.31639222
18  0.87847741
19  0.56690920
20 -0.34535250
21 -2.39701322
22  0.80800814
23  2.77654874
24  0.09803249
25 -0.31339440
26  2.31691496
27 -0.60682440
28 -1.26562285
29 -3.63888496
30 -0.87424980
31 -0.73984398
32  4.51674818
33  4.58021253
34  2.06775064
35 -2.38397392
36 -1.61836423
37 -2.83792726
38 -1.52228983
39 -3.37082604
40 -2.05206160
41 -1.26247495
42 -0.55983927
43  2.11808958
44 -0.89828023
45 -1.70889493
46  1.93184258
47  0.61084555
48  2.66633201
49  2.03285721
50  2.49876501
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>