I'm familiar with most of the techniques of regression modeling but had a problem with my last project which had 17 predictors and i was able to unravel very few interactions despite using most of the techniques that were there in some standard textbooks. I want an insight from those who have modelled fuzzy data --> logical tables and then tried to get some behavioral insights.
I don't mind coding my own R functions and possess a sound familiarity with Numerical Linear Algebra and Matrix theory. Secondly, i don't want to dig deep into books to find little useful. Any references that you provide will be pretty helpful
Please advise
-Dev
From: Berton Gunter <[EMAIL PROTECTED]>
To: devshruti pahuja <[EMAIL PROTECTED]>
Subject: Re: [R] Regression Modeling query
Date: Tue, 22 Jun 2004 13:44:13 -0700
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devshruti pahuja wrote:
> Hi All
>
> I received a raw data set with one record per tennis player (both male and
> female) and then i cured it by aggregation i.e by 4 age groups, 2 gender
> levels and 6 income levels. Gender and Income are categorical variables.
> Please advise me how to use 'R' to model this data set (Actually, i want to
> know the right regression technique and steps to do that, including removing
> outliers at the begining and looking for hidden interactions).
>
--- in which case, shouldn't we also sign and hand in the homework for you?
-- Bert
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