A few months ago, I did run my data on RMark to work on the robust design analysis.
I tried to run it again today with the new version 2.1.9, but it is giving me a problem to get the output.
Using default formula for c
S.dot.GammaDoublePrime.dot.GammaPrime.dot.p.time.session.N.session
STOP ERROR
Error in extract.mark.output(out, model, adjust, realvcv, vcvfile) :
MARK did not run properly. If error message was not shown, re-run MARK with invisible=FALSE
Any thoughts?
- Code: Select all
#convert inp file
rd.data=convert.inp("C:/R/RD/Qi 2-3 (5th fortnight-all days)_without calves and sightings(identified dolphins).inp",use.comments=T)
#Process data specifying primary and secondary capture occasions
time.intervals=c(0,0,0,0,0,3,0,0,3,0,3,0,0,0,3,0,0,0,0,0,3,0,0,0,0,3,0,0,0,0,12,0,0,0,3,0,0,0,0,0,0,3,0,0,3,0,0,6,0,0,0,0,0)
rd.process=process.data(rd.data,begin.time=1,model="Robust",time.intervals=time.intervals)
#Create the design data
rd.ddl=make.design.data(rd.process)
#add covariates
rd.ddl$p$season[rd.ddl$p$session==1]=1
rd.ddl$p$season[rd.ddl$p$session==4]=2
rd.ddl$p$season[rd.ddl$p$session==7]=3
rd.ddl$p$season[rd.ddl$p$session==10]=4
rd.ddl$p$season[rd.ddl$p$session==13]=1
rd.ddl$p$season[rd.ddl$p$session==16]=2
rd.ddl$p$season[rd.ddl$p$session==19]=3
rd.ddl$p$season[rd.ddl$p$session==31]=3
rd.ddl$p$season[rd.ddl$p$session==34]=4
rd.ddl$p$season[rd.ddl$p$session==37]=1
rd.ddl$p$season[rd.ddl$p$session==40]=2
rd.ddl$p$season[rd.ddl$p$session==46]=4
rd.ddl$c$season[rd.ddl$c$session==1]=1
rd.ddl$c$season[rd.ddl$c$session==4]=2
rd.ddl$c$season[rd.ddl$c$session==7]=3
rd.ddl$c$season[rd.ddl$c$session==10]=4
rd.ddl$c$season[rd.ddl$c$session==13]=1
rd.ddl$c$season[rd.ddl$c$session==16]=2
rd.ddl$c$season[rd.ddl$c$session==19]=3
rd.ddl$c$season[rd.ddl$c$session==31]=3
rd.ddl$c$season[rd.ddl$c$session==34]=4
rd.ddl$c$season[rd.ddl$c$session==37]=1
rd.ddl$c$season[rd.ddl$c$session==40]=2
rd.ddl$c$season[rd.ddl$c$session==46]=4
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==1]=1
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==4]=2
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==7]=3
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==10]=4
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==13]=1
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==16]=2
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==19]=3
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==31]=3
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==34]=4
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==37]=1
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==40]=2
rd.ddl$GammaDoublePrime$season[rd.ddl$GammaDoublePrime$time==46]=4
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==1]=1
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==4]=2
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==7]=3
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==10]=4
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==13]=1
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==16]=2
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==19]=3
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==31]=3
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==34]=4
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==37]=1
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==40]=2
rd.ddl$GammaPrime$season[rd.ddl$GammaPrime$time==46]=4
rd.ddl$S$season[rd.ddl$S$time==1]=1
rd.ddl$S$season[rd.ddl$S$time==4]=2
rd.ddl$S$season[rd.ddl$S$time==7]=3
rd.ddl$S$season[rd.ddl$S$time==10]=4
rd.ddl$S$season[rd.ddl$S$time==13]=1
rd.ddl$S$season[rd.ddl$S$time==16]=2
rd.ddl$S$season[rd.ddl$S$time==19]=3
rd.ddl$S$season[rd.ddl$S$time==31]=3
rd.ddl$S$season[rd.ddl$S$time==34]=4
rd.ddl$S$season[rd.ddl$S$time==37]=1
rd.ddl$S$season[rd.ddl$S$time==40]=2
rd.ddl$S$season[rd.ddl$S$time==46]=4
rd.ddl$p$Year[rd.ddl$p$session==1]=1
rd.ddl$p$Year[rd.ddl$p$session==4]=1
rd.ddl$p$Year[rd.ddl$p$session==7]=1
rd.ddl$p$Year[rd.ddl$p$session==10]=1
rd.ddl$p$Year[rd.ddl$p$session==13]=2
rd.ddl$p$Year[rd.ddl$p$session==16]=2
rd.ddl$p$Year[rd.ddl$p$session==19]=2
rd.ddl$p$Year[rd.ddl$p$session==31]=3
rd.ddl$p$Year[rd.ddl$p$session==34]=3
rd.ddl$p$Year[rd.ddl$p$session==37]=4
rd.ddl$p$Year[rd.ddl$p$session==40]=4
rd.ddl$p$Year[rd.ddl$p$session==46]=4
rd.ddl$c$Year[rd.ddl$c$session==1]=1
rd.ddl$c$Year[rd.ddl$c$session==4]=1
rd.ddl$c$Year[rd.ddl$c$session==7]=1
rd.ddl$c$Year[rd.ddl$c$session==10]=1
rd.ddl$c$Year[rd.ddl$c$session==13]=2
rd.ddl$c$Year[rd.ddl$c$session==16]=2
rd.ddl$c$Year[rd.ddl$c$session==19]=2
rd.ddl$c$Year[rd.ddl$c$session==31]=3
rd.ddl$c$Year[rd.ddl$c$session==34]=3
rd.ddl$c$Year[rd.ddl$c$session==37]=4
rd.ddl$c$Year[rd.ddl$c$session==40]=4
rd.ddl$c$Year[rd.ddl$c$session==46]=4
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==1]=1
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==4]=1
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==7]=1
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==10]=1
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==13]=2
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==16]=2
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==19]=2
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==31]=3
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==34]=3
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==37]=4
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==40]=4
rd.ddl$GammaDoublePrime$Year[rd.ddl$GammaDoublePrime$time==46]=4
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==1]=1
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==4]=1
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==7]=1
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==10]=1
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==13]=2
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==16]=2
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==19]=2
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==31]=3
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==34]=3
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==37]=4
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==40]=4
rd.ddl$GammaPrime$Year[rd.ddl$GammaPrime$time==46]=4
rd.ddl$S$Year[rd.ddl$S$time==1]=1
rd.ddl$S$Year[rd.ddl$S$time==4]=1
rd.ddl$S$Year[rd.ddl$S$time==7]=1
rd.ddl$S$Year[rd.ddl$S$time==10]=1
rd.ddl$S$Year[rd.ddl$S$time==13]=2
rd.ddl$S$Year[rd.ddl$S$time==16]=2
rd.ddl$S$Year[rd.ddl$S$time==19]=2
rd.ddl$S$Year[rd.ddl$S$time==31]=3
rd.ddl$S$Year[rd.ddl$S$time==34]=3
rd.ddl$S$Year[rd.ddl$S$time==37]=4
rd.ddl$S$Year[rd.ddl$S$time==40]=4
rd.ddl$S$Year[rd.ddl$S$time==46]=4
#View design matrix
rd.ddl
#Markovian emigration
rd.markovian.models=function()
{
S.dot=list(formula=~1)
S.season=list(formula=~season)
S.year=list(formula=~Year)
S.time=list(formula=~time)
p.time.session=list(formula=~-1+session:time,share=TRUE)
GammaDoublePrime.season=list(formula=~season)
GammaDoublePrime.year=list(formula=~Year)
GammaDoublePrime.dot=list(formula=~1)
GammaDoublePrime.time=list(formula=~time)
GammaPrime.season=list(formula=~season)
GammaPrime.year=list(formula=~Year)
GammaPrime.dot=list(formula=~1)
GammaPrime.time=list(formula=~time)
N.session=list(formula=~session)
cml=create.model.list("Robust")
results=mark.wrapper(cml,data=rd.process,ddl=rd.ddl,adjust=FALSE)
return(results)
}
rd.markovian.results=rd.markovian.models()
Many thanks,
Sergi