check the dimensions of your X and P matrices:
>dim(X)
[1] 21 9
>dim(P)
[1] 9 21
what you see is that the final row is *named* 26. It's actually row 21.
cheers,
On 10/29/07, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
> Hi All
>
> Maybe I dont understand it, but I would have expected that the design matrix
> has
> as many rows as there were observations available to fit the model.
> Below a small artificial dataset created, then one model fitted and the design
> matrix outputted, having 27 rows. Then I delete 6 obs, and fit the model on
> these 21 obs, but the design matrix that comes out has 26 rows?
>
> Thanks for your enlightenment.
>
> Toby
>
>
>
>
> y = c()
> x1 = c()
> x2 = c()
> idx = 1
> for (i in 1:3) {
> for (j in 1:3) {
> for (k in 1:3) {
> y[idx] = 30*i+10*j+100*i*j+30*k-60
> x1[idx] = i
> x2[idx] = j
> idx = idx+1
> }
> }
> }
>
> lm11 = lm(y ~ factor(x1)*factor(x2), x=1)
> summary(lm11)
> unique(predict(lm11))
>
> X = lm11$x; X
>
> P = solve(t(X)%*%X) %*% t(X); round(P,3)
>
>
> y[3] = NA
> y[6] = NA
> y[12] = NA
> y[18] = NA
> y[24] = NA
> y[27] = NA
>
> lm21 = lm(y ~ factor(x1)*factor(x2), x=1)
> summary(lm21)
> unique(predict(lm21))
>
> X = lm21$x; X
>
> P = solve(t(X)%*%X) %*% t(X); round(P,3)
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Tim Calkins
0406 753 997
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