importing/exporting into MARK

[amandarg]

I'm running a robust design model in RMARK and I'm having trouble with importing into MARK. When I import I get the error message that "number of groups specified < 1" What am I doing wrong? There should be two groups: males and females. thanks, Amanda

Code: Select all

#RMark analysis
#Load RMark package
library(RMark);
rm(list=ls())
cleanup(ask=FALSE)

#inport .inp
bentsadults=convert.inp("C:/R_robust/inpfiles/bentsfixed_final.inp",
group.df=data.frame(sex=c("Male", "Female")))

#Process the data so models can be analyzed
#Time intervals for 4 primary occasions (300+ collectors)
#use the format from MARK where you put in the x/60 for time intervals
time=c(0,0,0,0,0,0,.733,0,0,0,0,4.25,0,0,0,0,0,0,0,0,0,0,0,0,1.47,0,0,0,0,0,0,0,0,0,0,0,0,0,4.47,0,0,0,0,0,0,0,0,0,0,0,0,.9,0,0,0,0,0,0,0,0,0,0,0,0,0)

bentsadults.proc=process.data(bentsadults,model="RDFullHet",time.intervals=time,
groups="sex")
summary(bentsadults.proc)

#Create the design data
bentsadults.ddl=make.design.data(bentsadults.proc)

bentsadults.analysis=function()
{

#Create parameter specifications for formulas
S.dot=list(formula=~1)
S.group=list(formula=~group)
S.time=list(formula=~time)
S.grpbytime=list(formula=~group*time)

GammaDoublePrime.0=list(formula=~1,fixed=0)
GammaPrime.0=list(formula=~1,fixed=0)
#GammaDoublePrime.dot=list(formula=~1,fixed=0,share=TRUE)

#m(b)
p.dotsession=list(formula=~session+c,share=TRUE)

#p will be different ever session and c=p for each session
p.dotsession.c=list(formula=~session,share=TRUE)

#m(bh) diff each primary period
p.mixturesession=list(formula=~session:mixture+c,share=TRUE)

#m(h) diff each primary period
p.mixturesession.c=list(formula=~session:mixture,share=TRUE)

#m(t) different each primary period
p.dottimesession.c=list(formula=~session:time,share=TRUE)

#m(g) diff each primary period
p.dotgroup.c=list(formula=~session:group,share=TRUE)

#m(t*g) diff each primary period
p.timegroup.c=list(formula=~session:time*group,share=TRUE)

#m(th) diff each primary period
#p.timemixturesessionc=list(formula=~session:time+mixture,share=TRUE)

pi.session=list(formula=~session)
#no heterogeneity
pi.none=list(formula=~1, fixed=1)

N.session=list(formula=~session)

# create model list
cml=create.model.list("RDFullHet")
#row.names(cml)=c(1:length(cml$p))

# run and return models
results=mark.wrapper(cml,data=bentsadults.proc,ddl=bentsadults.ddl,adjust=TRUE)
return(results)
}

dummy=capture.output(bentsadults.results<-bentsadults.analysis())

summary(bentsadults.results)

bentsadults.results.table=bentsadults.results$model.table