R help - Dec 2013 - Get average model after dredge function ran in a loop

Dear all

I'm a beginner in R and I'm trying to get the final model after I run
the
dredge function for 10 times (with a loop):

###Building the Model
Coy.glm0<-glm(pa ~  shrub + snowdep + tree + bio5 + bio6 + bio12 +
log(human+1), data=Coy.pa, family=binomial)
summary(Coy.glm0)

install.packages('MuMIn')
library(MuMIn)
Coy.dredge<-dredge(Coy.glm0)
head(Coy.dredge) ######################Look in which colum is AIC
###Building a simulation
Coy.models<-Coy.dredge[1,c(1:13)]
Coy.models


###Turn a loop who will create 10 models
run=1
while(run<11) #<11 means 10 models.
{
  Coy.abs$Long<-runif(300,498,2579440)
  Coy.abs$Lat<-runif(300,-51483,1377669)
  Coy.pa<-rbind(Coy.train, Coy.abs)    ####???? train ou prSS
  Coy.ppp<-ppp(Coy.pa$Long,Coy.pa$Lat, window=win,
unitname="meters")
  Coy.pa$snowdep<-snowdepz.im[Coy.ppp, drop=F]
  Coy.pa$tree<-treez.im[Coy.ppp, drop=F]
  Coy.pa$bio5<-bio5z.im[Coy.ppp, drop=F]
  Coy.pa$bio6<-bio6z.im[Coy.ppp, drop=F]
  Coy.pa$bio12<-bio12z.im[Coy.ppp, drop=F]
  Coy.pa$human<-humanz.im[Coy.ppp, drop=F]
  Coy.pa$shrub<-shrub.im[Coy.ppp, drop=F]

  Coy.glm0<-glm(pa ~ shrub + snowdep + tree + bio5 +  bio6 + bio12+
log(human+1), data=Coy.pa, family=binomial)
  Coy.dredge<-dredge(Coy.glm0)
  Coy.models<-rbind(Coy.models, Coy.dredge[1,c(1:13)])
  run=run+1
}

I do get a best model for each run which I then hand pick and add to a
table. The problem is that I have 11 models now in this table and I want
their average to get the final model. I don't know how to do it from the
table (as the model.avg() will tell me I only have one model in the table,
because it's not recognizing the different rows as different models), but
on the other hand there must be a way to do it directly in the loop, only
I'm not sure at what point of the script I should be asking for it and how
the code should be written.

I would very much appreciate any help you can give me.

Thank you.

Cat

	[[alternative HTML version deleted]]

You are trying to average coefficients from models fitted to different
data (as you have manipulated Lat+Long values), you cannot do it using
AIC weights.

kamil



On 2013-12-11 11:00, r-help-request at r-project.org
wrote:
> Message: 26
> Date: Tue, 10 Dec 2013 15:44:28 -0500
> From: Catarina Ferreira<catferreira at gmail.com>
> To: r-help<r-help at r-project.org>
> Subject: [R] Get average model after dredge function ran in a loop
> Message-ID:
>       <CAAiga1sKpKS9aQHYs+RNrBWJxmxhRf3qn6DgaEN1P8QSt-293w at
mail.gmail.com>
> Content-Type: text/plain
>
> Dear all
>
> I'm a beginner in R and I'm trying to get the final model after I
run the
> dredge function for 10 times (with a loop):
>
> ###Building the Model
> Coy.glm0<-glm(pa ~  shrub + snowdep + tree + bio5 + bio6 + bio12 +
> log(human+1), data=Coy.pa, family=binomial)
> summary(Coy.glm0)
>
> install.packages('MuMIn')
> library(MuMIn)
> Coy.dredge<-dredge(Coy.glm0)
> head(Coy.dredge) ######################Look in which colum is AIC
> ###Building a simulation
> Coy.models<-Coy.dredge[1,c(1:13)]
> Coy.models
>
>
> ###Turn a loop who will create 10 models
> run=1
> while(run<11) #<11 means 10 models.
> {
>    Coy.abs$Long<-runif(300,498,2579440)
>    Coy.abs$Lat<-runif(300,-51483,1377669)
>    Coy.pa<-rbind(Coy.train, Coy.abs)    ####???? train ou prSS
>    Coy.ppp<-ppp(Coy.pa$Long,Coy.pa$Lat, window=win,
unitname="meters")
>    Coy.pa$snowdep<-snowdepz.im[Coy.ppp, drop=F]
>    Coy.pa$tree<-treez.im[Coy.ppp, drop=F]
>    Coy.pa$bio5<-bio5z.im[Coy.ppp, drop=F]
>    Coy.pa$bio6<-bio6z.im[Coy.ppp, drop=F]
>    Coy.pa$bio12<-bio12z.im[Coy.ppp, drop=F]
>    Coy.pa$human<-humanz.im[Coy.ppp, drop=F]
>    Coy.pa$shrub<-shrub.im[Coy.ppp, drop=F]
>
>    Coy.glm0<-glm(pa ~ shrub + snowdep + tree + bio5 +  bio6 + bio12+
> log(human+1), data=Coy.pa, family=binomial)
>    Coy.dredge<-dredge(Coy.glm0)
>    Coy.models<-rbind(Coy.models, Coy.dredge[1,c(1:13)])
>    run=run+1
> }
>
> I do get a best model for each run which I then hand pick and add to a
> table. The problem is that I have 11 models now in this table and I want
> their average to get the final model. I don't know how to do it from
the
> table (as the model.avg() will tell me I only have one model in the table,
> because it's not recognizing the different rows as different models),
but
> on the other hand there must be a way to do it directly in the loop, only
> I'm not sure at what point of the script I should be asking for it and
how
> the code should be written.
>
> I would very much appreciate any help you can give me.
>
> Thank you.
>
> Cat




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