From: Jorge Ivan Velez <jorgeivanvelez_at_gmail.com>

Date: Mon, 07 Jul 2008 20:08:49 -0400

R-help_at_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. Received on Tue 08 Jul 2008 - 00:11:54 GMT

Date: Mon, 07 Jul 2008 20:08:49 -0400

Dear Dhruv,

Try this:

# data set

set.seed(123)

X=matrix(rpois(10,10),ncol=2)

X

[,1] [,2] [1,] 8 15 [2,] 9 11 [3,] 14 5 [4,] 10 4 [5,] 10 13

# outcome

t(apply(X,1,function(x,betas){

if(length(x)!=length(betas)) stop("x and betas are of different length!")
y=x*betas

y

},betas=c(0.05,0.6)))

[,1] [,2] [1,] 0.40 9.0 [2,] 0.45 6.6 [3,] 0.70 3.0 [4,] 0.50 2.4 [5,] 0.50 7.8

**HTH,
**
Jorge

On Mon, Jul 7, 2008 at 7:56 PM, DS <ds5j_at_excite.com> wrote:

*>
**> Hi,
**>
*

> is there an easy way to get the calculated weights in a regression

*> equation?
**>
**>
**>
**> for e.g.
**>
**> if my model has 2 variables 1 and 2 with coefficient .05 and .6
**>
**> how can I get the computed values for a test dataset for each coefficient?
**>
**> data
**>
**> var1,var2
**>
**> 10,100
**>
**>
**>
**> so I want to get .5, 60 back in a vector. This is a one row example but I
**> would want to get a matrix of multiplied out coefficients and terms for use
**> in comparing contribution of variables to final score. As in a scorecard
**> using logistic regression.
**>
**>
**>
**> Please advise.
**>
**> thanks
**>
**> Dhruv
**>
**> ______________________________________________
**> R-help_at_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.
**>
*

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