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

varin sacha varinsacha at yahoo.fr
Wed Jul 6 10:15:40 CEST 2016


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>

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.



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