Re: [R] lm(y ~ group/x ) + predict.lm(...,type="terms")

2014-01-18 Thread Prof Brian Ripley
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)  group2group1:xgroup2: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  0.00
2 -18.098424  0.00
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"))

  groupgroup: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, UKFax:  +44 1865 272595

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and provide commented, minimal, self-contained, reproducible code.


[R] lm(y ~ group/x ) + predict.lm(...,type="terms")

2014-01-18 Thread Xing Zhao
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)  group2group1:xgroup2: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  0.00
2 -18.098424  0.00
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"))
 groupgroup: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

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


[R] lm(y ~ group/x ) + predict.lm(...,type="terms")

2014-01-18 Thread Xing Zhao
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)  group2group1:xgroup2: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  0.00
2 -18.098424  0.00
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"))
 groupgroup: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

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


[R] lm(y ~ group/x ) + predict.lm(...,type="terms")

2014-01-18 Thread Xing Zhao
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)  group2group1:xgroup2: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  0.00
2 -18.098424  0.00
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"))
 groupgroup: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

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.