[R] [RsR] How does "rlm" in R decide its "w" weights for each IRLSiteration?

Maheswaran Rohan mrohan at doc.govt.nz
Mon Jul 23 00:07:46 CEST 2012

Hi Valentin,

If the contamination is mainly in the response direction, M-estimator
provides good estimates for parameters and rlm can be used.


-----Original Message-----
From: r-sig-robust-bounces at r-project.org
[mailto:r-sig-robust-bounces at r-project.org] On Behalf Of Valentin
Sent: Saturday, 21 July 2012 6:57 a.m.
To: S Ellison
Cc: r-sig-robust at r-project.org; r-help
Subject: Re: [RsR] How does "rlm" in R decide its "w" weights for each

Hi Michael, S Ellison,

I do not actually understand what you want to achieve with the M
estimates of rlm in MASS, but why you do not give a try of lmrob in
'robustbase'. Please have a llok in the references (?lmrob) about the
advantages of MM estimators over the M estimators.

Best regards,

On Fri, Jul 20, 2012 at 5:11 PM, S Ellison <S.Ellison at lgcgroup.com>
>> -----Original Message-----
>> Subject: [RsR] How does "rlm" in R decide its "w" weights for
>> each IRLS iteration?
>> I am also confused about the manual:
>>            a.  The input arguments:
>> wt.method are the weights case weights (giving the relative
>> importance of case, so a weight of 2 means there are two of
>> these) or the inverse of the variances, so a weight of two
>> means this error is half as variable?
> When you give rlm weights (called 'weights', not 'w' on input, though
you can abbreviate to 'w'), you need to tell it which of these two
possibilities you used.
> If you gave it case numbers, say wt.method="case"; if you gave it
inverse variance weights, say wt.method="inv.var".
> The default is "inv.var".
>> The input argument "w" is used for the initial values of the
>> rlm IRLS weighting and the output value "w" is the converged "w".
> There is no input argument 'w' for rlm (see above).
> The output w are a  calculated using the psi function, so between 0
and 1.
> The effective weights for the final estimate would then be something
like w*weights, using the full name of the input argument (and if I
haven't forgotten a square root somewhere). At least, that would work
for a simple location estimate (eg rlm(x~1)).
>> If my understanding above is correct, how does "rlm" decide
>> its "w" for each IRLS iteration then?
> It uses the given psi functions to calculate the iterative weights
based on the scaled residuals.
>> Any pointers/tutorials/notes to the calculation of these
>> "w"'s in each IRLS iteration?
> Read the cited references for a detailed guide. Or, of course, MASS -
the package is, after all, intended to support the book, not replace it.
> S Ellison
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