[RsR] number of subsamples in robustbase::lmrob.S()

[Manuel Koller]

Dear Kaveh,

mts sets just the number of samples the algorithm tries before giving up finding a nonsingular subsample (if simple subsampling is used).
nResample is the parameter you want.

Best,

Manuel

On 1. May 2013, at 13:11 , Kaveh Vakili <kaveh.vakili using wis.kuleuven.be> wrote:

> 
> Dear All,
> 
> I'm trying to estimate the same model
> twice using the FastS with a varying
> # of ('simple') sub-samples. 
> 
> The man page for lmrob.control() defines 
> an option 'mts' which seems to be what I 
> want:
> 
> mts maximum number of samples to try in subsampling algorithm.
> 
> However, when trying on a dataset:
> 
> library(robustbase)
> #my data:
> n<-500
> p<-10
> x0<-matrix(rnorm(n*(p-1)),nc=p-1)
> y0<-rnorm(n)
> 
> s1<-lmrob.control()
> s1$subsampling<-"simple"
> s1$max.it<-500
> s1$k.max<-500
> s1$maxit.scale<-500
> 
> #\# subsamples?
> s1$mts<-10000
> system.time(lmrob.S(x=cbind(1,x0),y=y0,control=s1))
>  user  system elapsed 
>  0.084   0.000   0.081 
> #\# subsamples?
> s1$mts<-100
> system.time(lmrob.S(x=cbind(1,x0),y=y0,control=s1))
>  user  system elapsed 
>  0.076   0.000   0.077
> 
> 
> I find that the two timing are very close...I suspect 
> they both use a similar number of starting p-subsets 
> (and that I set the options in lmrob.control() wrongly). 
> 
> How can I check how many starting p-subsets were used 
> in each estimations?
> 
> Best regards,
> 
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