On Thu, Jul 7, 2011 at 5:24 PM, Dennis Murphy <djmu...@gmail.com> wrote:
> Hi:
>
> Here's another approach using the plyr package:
>
> library(plyr)
> df <- data.frame(gp = factor(rep(1:3, each = 4)), x = rnorm(12), y =
> rnorm(12))
> mylst <- split(df, df$gp)
> mycoefs <- ldply(mylst, function(d) coef(lm(y ~ x, data = d)))
> names(mycoefs) <- c('gp', 'intercept', 'slope')
> merge(df, mycoefs, by = 'gp', all.x = TRUE)
>
> One could write this more compactly as
>
> dfr <- merge(df, ldply(split(df, df$gp), function(d) coef(lm(y ~ x, data =
> d))),
> by.x = 'gp', by.y = '.id', all.x = TRUE)
Or even more compactly as
dfr <- merge(df, ddply(df, "gp", function(d) coef(lm(y ~ x, data = d))),
by.x = 'gp', by.y = '.id', all.x = TRUE)
Hadley
--
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University
http://had.co.nz/
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