Hi, I have a question about running multiple in regressions in R and then
storing the coefficients.  I have a large dataset with several variables,
one of which is a state variable, coded 1-50 for each state. I'd like to
run a regression of 28 select variables on the remaining 27 variables of
the dataset (there are 55 variables total), and specific for each state, ie
run a regression of variable1 on covariate1, covariate2, ..., covariate27
for observations where state==1. I'd then like to repeat this for variable1
for states 2-50, and the repeat the whole process for variable2,
variable3,..., variable28. I think I've written the correct R code to do
this, but the next thing I'd like to do is extract the coefficients,
ideally into a coefficient matrix. Could someone please help me with this?
Here's the code I've written so far, I'm not sure if this is the best way
to do this.  Please help me.

for (num in 1:50) {

    #PUF is the data set I'm using

#Subset the data by states
PUFnum <- subset(PUF, state==num)

#Attach data set with state specific data
attach(PUFnum)

#Run our prediction regression
    #the variables class1 through e19700 are the 27 covariates I want to use
regression <- lapply(PUFnum,  function(z) lm(z ~
class1+class2+class3+class4+class5+class6+class7+xtot+e00200+e00300+e00600+e00900+e01000+p04470+e04800+e09600+e07180+e07220+e07260+e06500+e10300+e59720+e11900+e18425+e18450+e18500+e19700))

Beta <- lapply(regression, function(d) d<- coef(regression$d))

 detach(PUFnum)

}
Thanks,
Mike

	[[alternative HTML version deleted]]

