Hello Uttara,
What happens if you try something like this?
Regression <-
read.table("C:/MUP/Internship/Distance_Statistics/Excel_data/Robust_Regression/ForModelling_Rev_Rob.csv",
sep= ",", header = TRUE)
library (MASS)
rfdmodel1 <- rlm(TotalEmployment_2004 ~ MISSISSIPPI + LOUISIANA +
TotalEmployment_2000 + PCWhitePop_2004 + UnemploymentRate_2004 +
PCUrbanPop2000 + PCPeopleWithACollegeDegree_2000 +
PCPopulation.of.or.over.65.years.of.age_2004, data = Regression)
summary(rfdmodel1)
Rather than using attach() on your data, you can just use the variable
name you assigned it to (here "Regression"), and pass that to the
'data' argument of rlm(). So the data that rlm() is fitting the model
to is "Regression", and the output of rlm() (that is the actual model)
is assigned to "rfdmodel1".
Hope that helps,
Josh
On Tue, Sep 21, 2010 at 8:02 AM, uttara_n <nilawar.utt...@gmail.com> wrote:
>
> I used the following command line:
>
> Regression <- read.table
> ("C:/MUP/Internship/Distance_Statistics/Excel_data/Robust_Regression/ForModelling_Rev_Rob.csv"
> , sep= ",", header = TRUE)
> attach (Regression)
> summary (Regression)
>
> library (MASS)
> rlm(TotalEmployment_2004 ~ MISSISSIPPI + LOUISIANA + TotalEmployment_2000 +
> PCWhitePop_2004 + UnemploymentRate_2004 + PCUrbanPop2000 +
> PCPeopleWithACollegeDegree_2000 +
> PCPopulation.of.or.over.65.years.of.age_2004, data = rfdmodel1)
>
> But, it is still giving me the same error.
>
> Uttara
> --
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>
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--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
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