At 09:41 28/09/2011, Elena Guijarro wrote:
Dear all,
I am not fluent in R and am struggling to 1) apply a lm to a weight-size
dataset, thus the model has to run separately for each species, each
year; 2) extract coefs, r-squared, n, etc. The data look like this:
year sps cm w
2009 50 16 22
2009 50 17 42
2009 50 18 45
2009 51 15 45
2009 51 16 53
2009 51 17 73
2010 50 15 22
2010 50 16 41
2010 50 16 21
2010 50 17 36
2010 51 15 43
2010 51 16 67
2010 51 17 79
The following script works for data from a single year, but I don't find
a way to subset the data by sps AND year and get the function running:
I think lmList from the nlme package does this for you. It comes with
some other helpful extractors or you can write your own as you have
done. Personally I would return a list rather than a vector but that
is a matter of taste.
f <- function(data) lm(log(w) ~ log(cm+0.5), data = data)
v <- lapply(split(data, data$sps), f)
and then I can extract the data with this script from Peter Solymos
(although I do not get the number of points used in the analysis):
myFun <-
function(lm)
{
out <- c(lm$coefficients[1],
lm$coefficients[2],
length(lm$run1$model$y),
summary(lm)$coefficients[2,2],
pf(summary(lm)$fstatistic[1], summary(lm)$fstatistic[2],
summary(lm)$fstatistic[3], lower.tail = FALSE),
summary(lm)$r.squared)
names(out) <- c("intercept","slope","n","slope.SE","p.value","r.squared")
return(out)}
results <- list()
for (i in 1:length(v)) results[[names(v)[i]]] <- myFun(v[[i]])
as.data.frame(results)
I have checked the plyr package, but the example that fits my data best
uses a for loop and I would like to avoid these. I have also tried the
following (among many other options) without results:
v<-tapply(data$w,list(data$cm,data$year),f)
Error in is.function(FUN) : 'FUN' is missing
Any ideas?
Thanks for your help,
Elena
[[alternative HTML version deleted]]
Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html
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