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

3 messages · Kaveh Vakili, Manuel Koller

#
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,
#
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 at wis.kuleuven.be> wrote:

            
#
Oh, Ok, thanks Manuel!
Sorry for having missed that out,

Best,
Kaveh
On 05/01/2013 05:32 PM, Manuel Koller wrote: