Hi Murray,

As you know, we’ve been doing mark-recapture trapping for foxes on 18 small grids for 3 years. I've been analyzing each year's data using multisession models, but now I’d like to do a comprehensive analysis, combining all data and considering years as groups. Thus, I included Yr as a categorical covariate in the capthist file (coding years as A, B, and C):

covariates(allyrs)

…

$`08_01`

Yr

F225 A

$`08_02`

Yr

F312 A

F98 A

M175 A

…

When I try to run models in which D or g0 vary by year, R crashes. For example, for either:

DyrG1S1g1s1HN <- secr.fit(allyrs,model=list(D~g,g0~1,sigma~1),start=c(-3,-3,-3,-2,5),buffer=2000,groups='Yr',detectfn=0)

D1GyrS1g1s1HN <- secr.fit(allyrs,model=list(D~1,g0~g,sigma~1), start=c(-3,-2,-2,-2,5),buffer=2000,groups='Yr',detectfn=0)

R crashes at this point, on multiple computers:

Checking data

Preparing detection design matrices

Preparing density design matrix

[R for Windows GUI front-end has encountered a problem and needs to close. We are sorry….]

I am able to run these data with Yr as an ind. covariate (e.g. D~Yr) with CL, but groups seem more appropriate. Is there a limitation on design matrix size? (I have 52 sessions total) Or do you see an error I'm making along the way?

Thanks for any assistance, Vickie