Dear all,
Could anyone help me figure out why bootstrap works for one of similar
models but not for the other and how I can solve it?
I am using R 2.11.1 in Windows and would like to get confidence
intervals for my models A and B by bootstrapping. However, bootstrap
gives expected output for the model A but not for B, which I found was
puzzling because the structure of the models is similar as I describe
below. I had another person running the models in another computer and
the same thing happens so this does not seem to be computer-specific.
I could not find a clue for a solution in the R archive or in the R
book (at least to the extent I understood).
Here are the properties of the models A and B and what happens when I
run bootstrap.
modelA: rA~stA1+ stA2+stA3
model B: rB~stB1+stB2+stB3
The variables for the models A and B are in the same dataset called
?data?. The sample size is 32 for both models and the value range and
distribution of the variables in the two models are similar.
(Variables from both models are at the end of this enquiry.)
[bootstrap of the model A]
A.fun<-function(data,indices)coefficients(lm(rA~stA1+
stA2+stA3,data=data[indices,]))
bootA<-boot(data,A.fun,1000);bootA
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = data, statistic = A.fun, R = 1000)
Bootstrap Statistics :
original bias std. error
t1* 1.00016501 -0.004350842 0.05309877
t2* 0.02343475 0.008501989 0.07638795
t3* -0.01602954 -0.004980400 0.07806805
t4* 0.03601194 -0.005417404 0.08510128
[bootstrap of the model B]
B.fun<-function(data,indices)coefficients(lm(rB~stB1+stB2+stB3),data=data[indices,])
bootB<-boot(data,B.fun,1000);bootB
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = data, statistic = B.fun, R = 1000)
Bootstrap Statistics :
original bias std. error
t1* 0.99975370 0 0
t2* -0.06091574 0 0
t3* 0.27506203 0 0
t4* -0.03040424 0 0
What am I missing here?
I highly appreciate any comments and suggestions.
Best Wishes,
Reiko Akiyama
Uppsala University
Sweden
[Variables from the model A]
rA
[1] 0.7100881 1.0406464 1.1100229 0.6182664 0.7345739 1.0577865 0.6856024
[8] 0.5264447 1.5793340 1.1793993 0.6488737 1.0214076 1.3589618 1.0528893
[15] 1.5242409 1.3761019 0.9427032 0.6794809 1.4752693 0.7737512 1.0120797
[22] 0.8692458 1.2079660 1.0610513 0.8570029 0.9794319 1.0957395 0.8243552
[29] 0.4162586 1.4079334 1.0692132 1.1059419
stA1
[1] -0.9126354 -0.8331680 -1.0239203 -0.3721959 -0.5311308 0.7564474
[7] -1.1828933 -1.2146727 -0.8172593 -0.9921410 -0.5152602 -0.9285442
[13] -0.4198840 -0.9444529 -0.4198840 -0.8331680 1.2810163 1.4081718
[19] 1.7102091 2.3460247 1.3806653 1.3127957 1.2333282 1.4240806
[25] -0.1337555 -0.1973142 0.2954372 -0.1337555 -0.4039753 -0.3880665
[31] 0.2795666 -0.2291317
stA2
[1] -0.2292617 -0.4917962 -0.6437899 -1.2241293 -0.3398026 -2.0946384
[7] -1.0721356 -1.2655821 -1.3484877 -1.8873744 -0.7543307 -0.9615948
[13] -0.3674378 0.4483537 0.8761467 -0.8786892 0.5312593 1.1524988
[19] 0.3234425 -0.4088906 0.5102565 1.1945044 1.7748438 0.6827002
[25] 0.6418001 1.1801340 0.4207184 0.8076114 0.9181522 0.6827002
[31] 0.9037819 0.9181522
stA3
[1] 0.86459627 -0.23416149 -2.00372671 0.04161491 0.78881988 -2.50869565
[7] -0.02608696 -0.84161491 -0.95465839 -0.28012422 0.47080745 0.07577640
[13] 0.84223602 0.24472050 2.83975155 0.43043478 -0.75652174 -0.92795031
[19] 0.29192547 -0.78633540 -0.78385093 -0.51242236 0.59627329 0.19068323
[25] 0.02919255 1.17018634 -0.19440994 0.68385093 1.08881988 -0.28385093
[31] -0.71118012 1.06583851
[Variables from the model B]
rB
[1] 1.5385568 1.5885100 1.3587255 0.8991566 1.4086787 0.3097095 0.9191378
[8] 0.3996252 0.7393065 0.6993440 1.2488286 1.4186693 1.4586318 1.8282851
[15] 0.8991566 0.9790816 1.0889785 1.0090535 0.7792690 0.8991566 0.8791753
[22] 0.7892597 0.6294096 0.9690910 1.0689973 0.5994377 0.6793628 0.7293159
[29] 0.9690910 0.7393065 0.7193253 1.7583507
stB1
[1] -0.67898627 -0.94275552 -1.32045796 0.03417996 -1.18276552 2.01872951
[7] -1.75937865 -1.85016395 -0.70319013 -0.89159673 -0.35055299 -0.38890124
[13] -0.81445562 -0.98941255 -0.95548269 -0.63066192 0.52759406 1.27063302
[19] 1.19746568 1.34424498 0.62679931 1.15103096 1.24195520 0.94395043
[25] 0.20232868 0.71085978 0.53654199 0.67470683 0.41377202 0.38428833
[31] 0.58178180 -0.40626910
stB2
[1] 2.18599646 1.64030436 0.29913150 -0.30874645 2.29052340 -2.13238029
[7] -0.78386750 -0.53233418 -0.96552917 -1.00046883 -0.02227346 -0.71399585
[13] 0.42490201 1.27034048 0.09650296 -0.32970563 -0.23188840 -0.24586119
[19] 0.04061179 -0.07118592 -0.49040812 -0.04323265 -0.06419952 -0.18297594
[25] 0.40393513 -0.73495504 -0.53233418 -0.23188840 0.13144263 -0.21092921
[31] -1.24501576 2.29052340
stB3
[1] -0.3683333 0.3416667 -1.7883333 -1.8133333 -0.6166667 0.8783333
[7] -1.4433333 -0.5150000 0.3066667 -0.5016667 -0.1850000 -0.2116667
[13] 1.2116667 -0.5783333 0.4533333 -0.3300000 -0.1733333 -0.7183333
[19] -0.5000000 -0.3983333 -1.2733333 -0.2333333 -0.2333333 -0.9150000
[25] 0.3366667 2.4200000 1.6016667 0.5116667 0.9283333 1.8750000
[31] 1.0866667 0.5950000
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