[R] lm design matrix bug?
toby909 at gmail.com
toby909 at gmail.com
Mon Oct 29 07:59:02 CET 2007
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)
More information about the R-help
mailing list