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Dear all, For an introductory course on glm?s I would like to create an example to show the difference between glm and transformation of the response. For this, I tried to create a dataset where the variance increases with the mean (as is the case in many ecological datasets): poissondata=data.frame( response=rpois(40,1:40), explanatory=1:40) attach(poissondata) However, I have run into

Good afternoon My name is Joanne Lenehan, I am a post grad at UNE using R version 2.9.0 I came across the Tweedie package in old R help posts and was interested in giving it a go for some data. The data is below and also attached as BaregroundLitterLogs Site Treatment Graze Dam Plot Time Bare Litter Logs 1 C remote yes 1 A 0 2 0 1 C remote yes 2 A 0 15 0 1 HE

#I am trying to understand how R fits models for contrasts in a #simple one-way anova. This is an example, I am not stupid enough to want #to simultaneously apply all of these contrasts to real data. With a few #exceptions, the tests that I would compute by hand (or by other software) #will give the same t or F statistics. It is the contrast estimates that R produces #that I can't seem to

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 have taken the liberty of including the R-help mailing list on this reply as that is the appropriate place to discuss lmer results. On 4/5/06, Andreas Svensson <andreas.svensson at bio.ntnu.no> wrote: > Hello again > I have now recieved some helpful hints in this matter and will summarize them but first let me reiterate the problem: > > I had two treatments: 2 types of food

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) >