Please see the posting guide: posting 3 times only reduces your chance
of an informative answer (as does posting in HTML). Your posting is too
vague for others to know what it is you do not understand.
R is Open Source: please read the sources for the definitive answer to
the 'know the computation process' query.
If (as I suspect) your difficulty is rather with interpreting terms in
formulae, study chapter 6 of MASS (Venables & Ripley, 2002).
On 18/01/2014 22:03, Xing Zhao wrote:
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 ).
'nested' ....
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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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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