Hi, all
I am trying to figure out the computation result for
predict.lm(...,type="terms") when the original fitting model has a
nesting term, lm(y ~ group/x ).
A example,
> set.seed(731)
> group <- factor(rep(1:2, 200))
> x <- rnorm(400)
>
> fun1 <- function(x) -3*x+8
> fun2 <- function(x) 15*x-18
>
> y <- (group==1)*fun1(x)+(group==2)*fun2(x) + rnorm(400)
>
> mod1 <- lm(y ~ group/(x-1) ) # without intercetp
> mod2 <- lm(y ~ group/x ) # with intercetp
>
>
> #data to predict
> new <- data.frame(x=rep(0:2,each=2),
+ group=factor(rep(1:2,3)))
> new
x group
1 0 1
2 0 2
3 1 1
4 1 2
5 2 1
6 2 2
> coef(mod1) # checking coefficients, both make sense to me.
group1 group2 group1:x group2:x
7.864981 -18.098424 -2.963931 15.051449
> coef(mod2)
(Intercept) group2 group1:x group2:x
7.864981 -25.963405 -2.963931 15.051449
>
> predict(mod1, new,type = c("response")) # two "response" type predictions
are the same, make sense to me.
1 2 3 4 5 6
7.864981 -18.098424 4.901050 -3.046975 1.937120 12.004474
> predict(mod2, new,type = c("response"))
1 2 3 4 5 6
7.864981 -18.098424 4.901050 -3.046975 1.937120 12.004474
>
> predict(mod1, new,type = c("terms")) # make sense to me
group group:x
1 7.864981 0.000000
2 -18.098424 0.000000
3 7.864981 -2.963931
4 -18.098424 15.051449
5 7.864981 -5.927861
6 -18.098424 30.102898
attr(,"constant")
[1] 0
# I want to know the computation process for group:x below??? this is
what I am interested in
> predict(mod2, new,type = c("terms"))
group group:x
1 12.9817 0.5209069
2 -12.9817 0.5209069
3 12.9817 -2.4430237
4 -12.9817 15.5723560
5 12.9817 -5.4069544
6 -12.9817 30.6238052
attr(,"constant")
[1] -5.637629
Thanks in advance
Xing
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