For a quick fix see ?try, in particular the last example there.

Afraid I am no expert in gls (which, you might mention, is in
package nlme) to explain the real cause of the problem.


> -----Original Message-----
> From: Christoph Lehmann [mailto:[EMAIL PROTECTED]
> Sent: 25 September 2003 12:32
> To: [EMAIL PROTECTED]
> Subject: [R] Error from gls call (package nlme)
> 
> 
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> ________________________________________________________________
> 
> Hi
> I have a huge array with series of data. For each cell in the array I
> fit a linear model, either using lm() or gls()
> 
> with lm() there is no problem, but with gls() I get an error:
> 
>       Error in glsEstimate(glsSt, control = glsEstControl) :
>               computed gls fit is singular, rank 2
> 
> as soon as there are data like this:
>       > y1 <- c(0,0,0,0)
>       > x1 <- c(0,1,1.3,0)
>       > gls(y1~x1)
>       Error in glsEstimate(glsSt, control = glsEstControl) :
>               computed gls fit is singular, rank 2
> 
> of course, this is not a problem for lm()
> 
>       > lm(y1~x1)
>  
>       Call:
>       lm(formula = y1 ~ x1)
>        
>       Coefficients:
>       (Intercept)           x1
>                 0            0
> 
> I know, that such data does not make "sense" but it is possible, that
> something like this occurs in my data-set. Since I call gls() 
> for every
> cell of my array in a loop, I don't want such errors to occur, since
> this breaks my loop.
> 
> what is the problem here? What are potential solutions?
> 
> Many thanks
> 
> Christoph
> -- 
> Christoph Lehmann <[EMAIL PROTECTED]>
> 
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>
 

Simon Fear
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