thanks Jorge. I appreciate your quick help.
Will this work if I have 20 columns of data but my regression only has 5
variables?
I am looking for something generic where I can give it my model and test data
and get back a vector of the multiplied coefficients (with no hard coding).
When predict is called with an input model and data, R must be multiplying all
co-efficients times variables and summing the number but is there a way to get
components of the regressiom terms stored in a matrix before they are added?
The idea is to build n models with various terms and after producing a
prediction list the top 3 variables that had the biggest impact in that
particular set of predictor values.
e.g. if I build a model to predict default of loans I would then need to list
the top factors in the model that can be used to explain why the loan is risky.
With 10-16 variables which can be present or not for each case there be a
different 2 or 3 variables that led to the said prediction.
Dhruv
--- On Mon 07/07, Jorge Ivan Velez < [EMAIL PROTECTED] > wrote:
From: Jorge Ivan Velez [mailto: [EMAIL PROTECTED]
To: [EMAIL PROTECTED]
Date: Mon, 7 Jul 2008 20:12:53 -0400
Subject: Re: [R] question on lm or glm matrix of coeficients X test data terms
Dear Dhruv,Try also:# data setset.seed(123)X=matrix(rpois(10,10),ncol=2)#
Function to estimate your
outcomeoutcome=function(x,betas){if(length(x)!=length(betas)) stop("x and betas
are of different length!")
y=x*betasy}# outcome for beta1=0.05 and
beta2=0.6t(apply(X,1,outcome,betas=c(0.05,0.6)))# outcome for beta1=5 and
beta2=6
t(apply(X,1,outcome,betas=c(5,6)))
HTH,JorgeOn Mon, Jul 7, 2008 at 7:56 PM, DS <[EMAIL PROTECTED]> 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
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