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robust regression

2 messages · Joerg Schaber, Brian Ripley

Original
Joerg Schaber
# 
Hi,

trying to do a robudt regression of a two-way linear model, I keep 
getting the following error:

 > lqs(obs ~ y + s -1,method="lms", contrasts=list(s=("contr.sum")))
Error: lqs failed: all the samples were singular

Robust regression with M-estimators works (also regular least square 
fits, of course):
rlm.formula(formula = obs ~ y + s - 1, method = "M", contrasts = list(s 
= ("contr.sum")))

I tried an exact sampling (psamp="exact"), but I keep getting syntax 
errors. Any idea how I can make the first one work?

Thanks,

joerg
Brian Ripley
#
On Wed, 30 Jul 2003, Joerg Schaber wrote:

            

      
      
      
    

        
You may well not be able to.  lms relies on being able to find a good fit 
to (just over) 50% of the data.  Sounds like you can't fit to 50%.
Try increasing `quantile'.

Generally resistant methods should be employed with caution for designed 
experiments (with factor covariates), and your specification of contrasts 
suggest y is a factor.  So this may not make statistical sense either.