search for: model_al

If I want to display a few polynomial regression fits I can do something like for (i in 1:6) { mod <- lm(y ~ poly(x,i)) print(summary(mod)) } Suppose that I don't want to over-write the fitted model objects, though. How do I create a list of blank fitted model objects for later use in a loop? Murray Jorgensen -- Dr Murray Jorgensen

I forgot to add that I first gave a starting value for K. Nonlinear least squares won't work because my errors are not normally distributed. Any advide on my maximum likelihood function would be greatly appreciated. ---------------------------- Original Message ---------------------------- Subject: RE: [R] maximum likelihood problem From: "Ravi Varadhan" <rvaradhan at

Hi R-listers, I have developed 47 GLM models with different combinations of interactions from 1 variable to 5 variables. I have manually made each model separately and put them into individual tables (organized by the number of variables) showing the AIC score. I want to compare all of these models. 1) What is the best way to compare various models with unique combinations and different number

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >