Displaying 6 results from an estimated 6 matches for "model7".
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2008 Nov 25
4
glm or transformation of the response?
...lanatory,poissondata)
model2=lm(sqrt(response+0.5)~explanatory,poissondata)
model3=lm(log(response+1)~explanatory,poissondata)
model4=glm(response~explanatory,poissondata,family=poisson)
model5=glm(response~explanatory,poissondata,family=quasipoisson)
model6=glm.nb(response~explanatory,poissondata)
model7=glm(response~explanatory,quasi(variance="mu",link="identity"))
plot(explanatory,response,pch=16)
lines(explanatory,predict(model1,explanatory=explanatory))
lines(explanatory,(predict(model2,explanatory=explanatory))^2-0.5,lty=2)
lines(explanatory,exp(predict(model3,explanatory...
2010 Jan 11
0
tweedie.profile error message
...tweedie.profile function
but keep getting the following:
Code entered:
require(statmod)
require(tweedie)
out<-with(bobB, tweedie.profile(Litter~Treatment*Time*Site,
p.vec=seq(1.05,1.95, length=10), method="interpolation", do.ci=TRUE,
do.smooth=TRUE, do.plot=TRUE))
out$p.max
model7<-(with(bobB, glm(Litter~Treatment*Time*Site,
family=tweedie(var.power=out$p.max, link.power=0))))
print(anova(model7, test="Chisq"))
summary(model7)
par(mfrow=c(2,2))
plot(model7)
BUT get
> out<-with(bobB, tweedie.profile(Litter~Treatment*Time*Site,
p.vec=seq(1.1,1.9, lengt...
2010 Sep 29
1
Understanding linear contrasts in Anova using R
#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
2012 Jan 25
6
How do I compare 47 GLM models with 1 to 5 interactions and unique combinations?
...ed - Event of exhumation
Sector - number measurements along the beach
Rayos - major sections of beach (grouped sectors)
TotalEggs - nest egg density
Example of how all models were created:
Model2.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ Aeventexhumed,
data=data.to.analyze, family=binomial)
Model7.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ HTL:Veg, family =
binomial, data.to.analyze)
Model21.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ HTL:Veg:TotalEggs,
data.to.analyze, family = binomial)
Model37.glm <- glm(cbind(Shells, TotalEggs-Shells) ~
HTL:Veg:TotalEggs:Aeventexhumed, data.t...
2006 Apr 16
0
[S] Problems with lme and 2 levels of nesting:Summary
...er situations in which these models are applied. The preferred
approach to model-building in R/S-PLUS is to build the model
sequentially. I would use
fm1 <- lmer(DeathDay ~ Treatment + (1|Clutch:Cup) + (1|Clutch))
fm2 <- lmer(DeathDay ~ 1 + (1|Clutch:Cup) + (1|Clutch)) # equivalent
to your model7
fm3 <- lmer(DeathDay ~ 1 + (1|Clutch))
and then compare fm2 and fm3, say with anova(fm2, fm3). As described
below the p-value from the likelihood ratio test in this case is not
exact because the hypothesis you are testing is on the boundary of the
parameter space. However, the value returned...
2012 Jan 18
4
R-Help
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)
>