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 ?
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
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