Creating a for-loop where i identifies data by column in R -

i trying use for-loop create series of summaries of gam models of variation in capture rate of invertebrate species using smoothed term day of year (doy), , linear predictor incorporating weather (there many of these). have made function run , output model summary:

gamlin <- function(x) {   m <- gam(log10e ~ s(doy) + x, data=eggseasongam)   return(summary(m)) } 

i think want utilize above in for-loop sequentially take x weather predictors in columns 4 through 173, struggling this. suggestions appreciated.

thanks, mike

2 approaches off top of head be:

t<-data.frame(c1=rnorm(10),c2=rnorm(10), c3=rnorm(10)) 

1- use formula, allows provide character string formula

> f<-function(d,x) lm(formula(paste("c1",x,sep="~")), data=d) > f(t,"c2")  call: lm(formula = formula(paste("c1", x, sep = "~")), data = d)  coefficients: (intercept)           c2     -0.1567      -0.4654 

2- alternatively feed in column directly

> f2<-function(d,x) lm(c1 ~ d[,x], data=d) > f2(t,"c2")  call: lm(formula = c1 ~ d[, x], data = d)  coefficients: (intercept)       d[, x]     -0.1567      -0.4654 

once have settled on approach dynamic regression function can put in for-loop

 for(col in 4:173) f(t,col) 

chances are, want use results somehow, rather print summary (perhaps take coefficients , put them in dataframe , graph them, or along lines. in case suggest checking out plyr , reshape packages , specficially functions melt , ddply within each

in case follows

library(melt) library(plyr)  yvar<-t[,1] xvars<-melt(t[,-1]) > head(xvars)   variable      value 1       c2 -0.8200263 2       c2 -1.5359220 3       c2 -0.2107913 4       c2 -0.2950263 5       c2  0.8231989 6       c2 -0.5971358  betas<-ddply(xvars, .(variable), summarize, beta=coefficients(lm(yvar ~ value))[2])