[R] how to take this experiment with R?

[Austin, Matt]

My mistake, you can't use the structure I proposed with lm() in combination
with step().

If what was suggested earlier by Gabor was not what you wanted, and instead
you want the 'best' three variable model, then it may be easier to use the
leaps package.  


> library(leaps)
> x     <- data.frame(matrix(rnorm(1550),c(50,31)))
> model <- regsubsets(y=x[,1], x=x[,2:31])
> m1    <-summary(model, matrix=TRUE, matrix.logical=TRUE)
> apply(m1$outmat, 1, which)[3]
$"3  ( 1 )"
X10 X14 X15 
  9  13  14 

> lm.fit(x=as.matrix(x[,as.vector(unlist(apply(m1$outmat, 1,
which)[3])+1)]), y=x[,1])
$coefficients
       X10        X14        X15 
-0.2694923 -0.4055546 -0.2692063 


--Matt
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Gabor Grothendieck
Sent: Monday, September 20, 2004 21:57 PM
To: 0034058 at fudan.edu.cn; r-help at stat.math.ethz.ch
Subject: Re: [R] how to take this experiment with R?




Suppose you just wanted variables 2,4 and 7 (which are in columns
3, 5 and 8, respectively).  Then you could do this:

   lm(X1 ~ X2 + X4 + X7, x)
or
   lm(X1 ~., x[,c(2,4,7)+1])


Date:   	Tue, 21 Sep 2004 12:27:38 +0800
From:   	rongguiwong <0034058 at fudan.edu.cn>
To:   	<r-help at stat.math.ethz.ch>
Subject:   	Re: [R] how to take this experiment with R?

ÔÚ 2004Äê9ÔÂ21ÈÕ ÐÇÆÚ¶þ 12:10£¬Gabor Grothendieck дµÀ£º
it works.
but i come across anather problem.
i just wnat to select 3 of the best indepent variables.
but the reslut from step(lm(X1 ~., x)) is :

Step: AIC= -37.64
X1 ~ X2 + X3 + X4 + X8 + X10 + X11 + X13 + X14 + X15 + X18 +
X21 + X22 + X25 + X26 + X27 + X29 + X30 + X31

Df Sum of Sq RSS AIC
<none> 11.014 -37.642
- X8 1 0.559 11.574 -37.165
- X27 1 0.867 11.881 -35.853
- X2 1 0.971 11.986 -35.416
- X18 1 0.978 11.992 -35.390
- X31 1 1.122 12.136 -34.793
- X10 1 1.400 12.414 -33.659
- X15 1 1.563 12.578 -33.005
- X29 1 1.608 12.622 -32.828
- X13 1 1.805 12.819 -32.055
- X30 1 1.880 12.894 -31.763
- X4 1 2.368 13.382 -29.906
- X14 1 2.495 13.509 -29.433
- X3 1 2.983 13.997 -27.659
- X22 1 2.999 14.013 -27.600
- X21 1 3.377 14.391 -26.271
- X25 1 4.323 15.338 -23.086
- X11 1 6.775 17.789 -15.672
- X26 1 7.232 18.246 -14.403

> You can express your model like this:
>
>
>
> lm(X1 ~., x)
>
>
>
> ?formula gives some help on formulas although the . notation
>
> above does not seem to be referred to there.
>
>
>
>
>
> Date:      Tue, 21 Sep 2004 11:52:04 +0800
>
> From:      rongguiwong <0034058 at fudan.edu.cn>
>
> To:      <r-help at stat.math.ethz.ch>
>
> Subject:      [R] how to take this experiment with R?
>
>
>
> i want to generate 30 independent variables and 1 dependent variable,each
> has
>
> 50 draws from a unit normal distribution.
>
> then, searching for the independent variables that together would do the
> best
>
> job for fitting the denpendent variabe.
>
>
>
> my way to generate the data is.
>
> x<-data.frame(matrix(rnorm(1550),c(50,31)))
>
> but is there more better way to do it?
>
>
>
> i want to use the followling is to search the model.
>
> model<-step(lm(X1~X2+X3+X4.....))
>
> but i don't know the to express the formula with lm function.i think there
> is
>
> a way the express it efficently.
>
> i try ?lm .but on result be found.
>
>
>
> any help is welcome!
>

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