On 6/2/12 19:36 , peter dalgaard wrote:
Actually, I think the issue is slightly different: IDL assumes that
the errors _are_ something (notice that setting measure_errors to 1
is not equvalent to omitting them), R assumes that they are
_proportional_ to the inverse weights
Yes, I think this i
On Feb 6, 2012, at 10:57 , Achim Zeileis wrote:
> On Mon, 6 Feb 2012, James Annan wrote:
>
>
> The summary() shows under "Residuals" the contributions to the objective
> function, i.e. sqrt(1/w) (y - x'b) in the notation above.
>
> However, by using the residuals extractor function you can ge
On Mon, 6 Feb 2012, James Annan wrote:
I am trying to use lm for a simple linear fit with weights. The results
I get from IDL (which I am more familiar with) seem correct and
intuitive, but the "lm" function in R gives outputs that seem strange to
me.
Unweighted case:
x<-1:4
y<-(1:4)^2
sum
I am trying to use lm for a simple linear fit with weights. The results
I get from IDL (which I am more familiar with) seem correct and
intuitive, but the "lm" function in R gives outputs that seem strange to me.
Unweighted case:
> x<-1:4
> y<-(1:4)^2
> summary(lm(y~x))
Call:
lm(formula = y ~
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