secr_wolverine: analysis of the wolverine data using secr
In jaroyle/SCRbayes: Bayesian analysis of spatial capture-recapture models

analysis using secr

1	secr_wolverine()

##
## The function executes a set of commands to conduct a
## likelihood analysis of the wolverine camera trapping data
## the function returns the results for the 2 x 2 habitat mask
##

## The function is currently defined by the following set of commands:


library("secr")
library("scrbook")
data("wolverine")
traps<-as.matrix(wolverine$wtraps)   #[,1:3]
dimnames(traps)<-list(NULL,c("trapID","x","y",paste("day",1:165,sep="")))

traps1<-as.data.frame(traps[,1:3])
traps1$x<-as.numeric(as.character(traps1$x))
traps1$y<-as.numeric(as.character(traps1$y))

# This seems to ignore the trap operation information
trapfile1<-read.traps(data=traps1,detector="proximity")

trapfile2<-scr2secr(scrtraps=traps,type="proximity")

wolv.dat<-wolverine$wcaps
dimnames(wolv.dat)<-list(NULL,c("Session","ID","Occasion","trapID"))
wolv.dat<-as.data.frame(wolv.dat)
wolvcapt1<-make.capthist(wolv.dat,trapfile1,fmt="trapID",noccasions=165)
wolvcapt2<-make.capthist(wolv.dat,trapfile2,fmt="trapID",noccasions=165)

gr<-(as.matrix(wolverine$grid2))
dimnames(gr)<-list(NULL,c("x","y"))
gr2<-read.mask(data=gr)

gr<-(as.matrix(wolverine$grid4))
dimnames(gr)<-list(NULL,c("x","y"))
gr4<-read.mask(data=gr)

gr<-(as.matrix(wolverine$grid8))
dimnames(gr)<-list(NULL,c("x","y"))
gr8<-read.mask(data=gr)

# run model without trap operation information
wolv.secr<-secr.fit(wolvcapt1,model=list(D~1, g0~1, sigma~1), buffer=20000)

# now use wolvcapt2 which has trap operation information
wolv.secr0<-secr.fit(wolvcapt2,model=list(D~1, g0~1, sigma~1), buffer=20000)
wolv.secr2<-secr.fit(wolvcapt2,model=list(D~1, g0~1, sigma~1), buffer=20000,mask=gr2)
wolv.secr4<-secr.fit(wolvcapt2,model=list(D~1, g0~1, sigma~1), buffer=20000,mask=gr4)
wolv.secr8<-secr.fit(wolvcapt2,model=list(D~1, g0~1, sigma~1), buffer=20000,mask=gr8)
 

# reported in the book chapter:
wolv.secr2