I've used lm()
to fit multiple regression models, for multiple (~1 million) response variables in R. Eg.
allModels <- lm(t(responseVariablesMatrix ~ modelMatrix)
This returns an object of class "mlm", which is like a huge object containing all the models. I want to get the Residual Sum of Squares for each model, which I can do using:
summaries <- summary(allModels)
rss1s <- sapply(summaries, function(a) return(a$sigma))
My problem is that I think the "summary" function calculates a whole bunch of other stuff, too, and is hence quite slow. I'm wondering if there is a faster way of extracting just the Residual sum of squares for the model?
Thanks!