Bill Simpson <wsimpson at uwinnipeg.ca> writes:
>
> This surprised me. Is it the way it is supposed to be?
> > x<-c(1,2,3,4,5)
> > y<-c(1.2,1.3,1.4,1.5,NA)
> > x-y
> [1] -0.2 0.7 1.6 2.5 NA
> > (x-y)^2
> [1] 0.04 0.49 2.56 6.25 NaN
> >>>so NA^2 = NaN? Why not still NA?
>
> > sum((x-y)^2)
> [1] NaN
> >>>yes that is reasonable
>
> So if you ever have a data set with missing observations (NAs), you
can't
> do any nlm() least squares fitting? That doesn't seem right.
Bug, disappeared in current intermediate patch version.
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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