Dimitri -
Without commenting on the wiseness of such an approach,
here's one way to do what you want:
regs = lapply(predictors,function(var)lm(data$y~data[,var]))
names(regs) = predictors
Now
regs[['x1']] holds the lm output from the regression of y on x1,
regs[['x2']] holds the lm output from the regression of y on x2, etc.
Suppose you wanted to know what the slopes for each regressor were.
First, find what you want for one:
coef(regs[['x1']])[2]
Next, write a function to extract this information:
getslope = function(reg)coef(reg)[2]
Now use sapply to get all the slopes of the individual regressions:
sapply(regs,getslope)
Hope this helps.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
[email protected]
On Tue, 9 Mar 2010, Dimitri Liakhovitski wrote:
Dear R-ers,
I have a data frame data with predictors x1 through x5 and the
response variable y.
I am running a simple regression:
reg<-lm(y~x1, data=data)
I would like to loop through all predictors. Something like:
predictors<-c("x1","x2",... "x10)
for(i in predictors){
reg<-lm(y~i)
etc.
}
But it's not working. I am getting an error:
Error in model.frame.default(formula = Y ~ x1 + x2 + x3 + i, data = sample, :
variable lengths differ (found for 'i')
How can I make it take predictor names in the lm formula?
Thank you!
--
Dimitri Liakhovitski
Ninah.com
[email protected]
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