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

[Michael]

Hi all,

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?

w (optional) initial down-weighting for each case.

init (optional) initial values for the coefficients OR a method to find
initial values OR the result of a fit with a coef component. Known methods
are "ls" (the default) for an initial least-squares fit using weights
w*weights, and "lts" for an unweighted least-trimmed squares fit with 200
samples.



b. The returned values:

w the weights used in the IWLS process

wresid a working residual, weighted for "inv.var" weights only.



How to use these input arguments?

Anybody please shed some light?

Also, is my understanding below correct?

The input argument "w" is used for the initial values of the rlm IRLS
weighting and the output value "w" is the converged "w".

The "weights" input argument is actually what I want to apply - if I have
my own set of weights.
And the real/actual weights are the product of "weights"(I supplied) and
the converged output "w" (an output).


If my understanding above is correct, how does "rlm" decide its "w" for
each IRLS iteration then?

Any pointers/tutorials/notes to the calculation of these "w"'s in each IRLS
iteration?

Thanks to all.

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