On 1/20/2012 1:42 AM, Berwin A Turlach wrote:
One reason that I can see for people to use zero weights rather than
'subset' is that fitted() and predict() in the former case readily
produce fitted values for the observations that received a zero weight.
Another is that including the case of zero
G'day Brian,
On Fri, 20 Jan 2012 06:20:30 +
Prof Brian Ripley wrote:
> I do wonder why people use zero weights rather than 'subset', and I
> don't particularly like the discontinuity as a weight goes to zero.
I completely agree, and for developers it is a bit of a pain to make
sure that al
I do wonder why people use zero weights rather than 'subset', and I
don't particularly like the discontinuity as a weight goes to zero.
But this came up for glm() and it would be better to be consistent, so
thanks for pointing out the nls() cases. We'll alter them.
On 20/01/2012 05:30, Berwi
Dear all,
I am studying a bit the various support functions that exist for
extracting information from fitted model objects.
>From the help files it is not completely clear to me whether the number
returned by nobs() should be the same as the "nobs" attribute of the
object returned by logLik().
