[R] BCa Bootstrapped regression coefficients from lmrob function not working

peter dalgaard pdalgd at gmail.com
Wed Jul 6 11:05:44 CEST 2016 

Offhand, I would suspect that the cause is that earth() does not return a coefficient vector of the same length in every bootstrap iteration (_adaptive_ regression splines). This makes the bootstrap rather tricky to even define.

-pd

> On 06 Jul 2016, at 10:15 , varin sacha <varinsacha at yahoo.fr> wrote:
> 
> Dear Bert,
> 
> You are right.
> 
>> results=boot(data=newdata, statistic=boot.MARS, R=1000,formula=PIBparHab ~ QUALITESANSREDONDANCE + competitivite + innovation)
> Erreur dans boot(data = newdata, statistic = boot.MARS, R = 1000, formula = PIBparHab ~  : 
> le nombre d'objets à remplacer n'est pas multiple de la taille du remplacement 
> 
> In English it would be something like : number of items to replace is not a multiple of replacement length
> 
> 
> Best
> S
> 
> ________________________________
> De : Bert Gunter <bgunter.4567 at gmail.com>
> À : varin sacha <varinsacha at yahoo.fr> 
> Cc : peter dalgaard <pdalgd at gmail.com>; R-help Mailing List <r-help at r-project.org>
> Envoyé le : Mercredi 6 juillet 2016 1h19
> Objet : Re: [R] BCa Bootstrapped regression coefficients from lmrob function not working
> 
> 
> It would help to show your  error message, n'est-ce pas?
> 
> Cheers,
> Bert
> 
> 
> Bert Gunter
> 
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
> 
> 
> On Tue, Jul 5, 2016 at 2:51 PM, varin sacha via R-help
> <r-help at r-project.org> wrote:
>> Dear Professor Dalgaard,
>> 
>> I really thank you lots for your response. I have solved my problem. Now, I have tried to do the same (calculate the BCa bootstrapped CIs) for the MARS regression, and I get an error message. If somebody has a hint to solve my problem, would be highly appreciated.
>> 
>> Reproducible example :
>> 
>> 
>> Dataset = data.frame(PIBparHab=c(43931,67524,48348,44827,52409,15245,24453,57636,28992,17102,51495,47243,40908,22494,12784,48391,44221,32514,35132,46679,106022,9817,99635,38678,49128,12876,20732,17151,19670,41053,22488,57134,83295,10660),
>> 
>> QUALITESANSREDONDANCE=c(1082.5,1066.6,1079.3,1079.9,1074.9,1008.6,1007.5,1111.3,1108.2,1109.7,1059.6,1165.1,1026.7,1035.1,997.8,1044.8,1073.6,1085.7,1083.8,1021.6,1036.2,1075.3,1069.3,1101.4,1086.9,1072.1,1166.7,983.9,1004.5,1082.5,1123.5,1094.9,1105.1,1010.8),
>> 
>> competitivite=c(89,83,78,73,90,71,77,85,61,67,98,82,70,43,57,78,72,79,61,71,86,63,90,75,87,64,60,56,66,80,53,91,97,62),
>> 
>> innovation=c(56,52,53,54,57,43,54,60,47,55,58,62,52,35,47,59,56,56,45,52,58,33,57,57,61,40,45,41,50,61,50,65,68,34))
>> 
>> install.packages("earth")
>> 
>> library(earth)
>> 
>> newdata=na.omit(Dataset)
>> 
>> model=earth(PIBparHab ~ QUALITESANSREDONDANCE + competitivite + innovation,data=newdata)
>> 
>> summary(model)
>> 
>> plot(model)
>> 
>> plotmo(model)
>> 
>> 
>> boot.MARS=function(formula,data,indices) {
>> 
>> d=data[indices,]
>> 
>> fit=earth(formula,data=d)
>> 
>> return(coef(fit))
>> 
>> }
>> 
>> library(boot)
>> 
>> results=boot(data=newdata, statistic=boot.MARS, R=1000,formula=PIBparHab ~ QUALITESANSREDONDANCE + competitivite + innovation)
>> 
>> boot.ci(results, type= "bca",index=2)
>> 
>> 
>> Best,
>> S
>> 
>> ________________________________
>> De : peter dalgaard <pdalgd at gmail.com>
>> 
>> Cc : R-help Mailing List <r-help at r-project.org>
>> Envoyé le : Dimanche 3 juillet 2016 18h19
>> Objet : Re: [R] BCa Bootstrapped regression coefficients from lmrob function not working
>> 
>> 
>> 
>>> On 03 Jul 2016, at 13:47 , varin sacha via R-help <r-help at r-project.org> wrote:
>>> 
>>> Dear R-experts,
>>> 
>>> I am trying to calculate the bootstrapped (BCa) regression coefficients for a robust regression using MM-type estimator (lmrob function from robustbase package).
>>> 
>>> My R code here below is showing a warning message ([1] "All values of t are equal to
>>> 22.2073014256803\n Can not calculate confidence intervals" NULL), I was wondering if it was because I am trying to fit a robust regression with lmrob function rather than a simple lm ? I mean maybe the boot.ci function does not work with lmrob function ? If not, I was wondering what was going on ?
>> 
>> You need to review your code. You calculate a,b,c,d in the global environment and create newdata as a subset of Dataset, then use a,b,c,d in the formula, but no such variables are in newdata. AFAICT, all your bootstrap fits use the _same_ global values for a,b,c,d hence give the same result 1000 times...
>> 
>> -pd
>> 
>> 
>> 
>>> 
>>> Here is the reproducible example
>>> 
>>> 
>>> Dataset = data.frame(PIBparHab=c(43931,67524,48348,44827,52409,15245,24453,57636,28992,17102,51495,47243,40908,22494,12784,48391,44221,32514,35132,46679,106022,9817,99635,38678,49128,12876,20732,17151,19670,41053,22488,57134,83295,10660),
>>> 
>>> QUALITESANSREDONDANCE=c(1082.5,1066.6,1079.3,1079.9,1074.9,1008.6,1007.5,1111.3,1108.2,1109.7,1059.6,1165.1,1026.7,1035.1,997.8,1044.8,1073.6,1085.7,1083.8,1021.6,1036.2,1075.3,1069.3,1101.4,1086.9,1072.1,1166.7,983.9,1004.5,1082.5,1123.5,1094.9,1105.1,1010.8),
>>> 
>>> competitivite=c(89,83,78,73,90,71,77,85,61,67,98,82,70,43,57,78,72,79,61,71,86,63,90,75,87,64,60,56,66,80,53,91,97,62),
>>> 
>>> innovation=c(56,52,53,54,57,43,54,60,47,55,58,62,52,35,47,59,56,56,45,52,58,33,57,57,61,40,45,41,50,61,50,65,68,34))
>>> 
>>> library("robustbase")
>>> newdata=na.omit(Dataset)
>>> a=Dataset$PIBparHab
>>> b=Dataset$QUALITESANSREDONDANCE
>>> c=Dataset$competitivite
>>> d=Dataset$innovation
>>> 
>>> fm.lmrob=lmrob(a~b+c+d,data=newdata)
>>> fm.lmrob
>>> 
>>> boot.Lmrob=function(formula,data,indices) {
>>> d=data[indices,]
>>> fit=lmrob(formula,data=d)
>>> return(coef(fit))
>>> }
>>> 
>>> library(boot)
>>> results=boot(data=newdata, statistic=boot.Lmrob, R=1000,formula=a~b+c+d)
>>> boot.ci(results, type= "bca",index=2)
>>> 
>>> 
>>> Any help would be highly appreciated,
>>> S
>>> 
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>> 
>> --
>> Peter Dalgaard, Professor,
>> Center for Statistics, Copenhagen Business School
>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>> Phone: (+45)38153501
>> Office: A 4.23
>> Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com
> 
>> 
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.

-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com

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