Thank you for your response, Dr. Ken. Please find the code and the output below:
y6OF_3 <- c('~OS_Z+AG_Z','~OS_Z','~Dog_Z') # OS and AG: habitat types proportion within grid-cell; Dog: free-ranging dog capture rates
> y6_3 <- occuMulti(yDF,y6OF_3,data6, se = T, silent = T, penalty = 1)
Bootstraping covariance matrix
> #Look at output
> summary(y6_3)
Call:
occuMulti(detformulas = yDF, stateformulas = y6OF_3, data = data6,
penalty = 1, se = T, silent = T, maxOrder = 2L)
Occupancy (logit-scale):
Estimate SE z P(>|z|)
[sp1] (Intercept) -0.607 0.398 -1.52 1.27e-01
[sp1] OS_Z 0.594 0.380 1.56 1.18e-01
[sp1] AG_Z -0.412 0.245 -1.68 9.23e-02
[sp2] (Intercept) -1.599 0.342 -4.67 2.99e-06
[sp2] OS_Z 0.524 0.182 2.88 4.00e-03
[sp1:sp2] (Intercept) 0.554 0.459 1.21 2.27e-01
[sp1:sp2] Dog_Z -0.488 0.339 -1.44 1.49e-01
Detection (logit-scale):
Estimate SE z P(>|z|)
[sp1] (Intercept) -3.58432 0.2259 -15.866 1.10e-56
[sp1] TrepZ:OCCT 1.14998 0.2370 4.851 1.23e-06
[sp1] TrepZ:OCSS 0.18588 0.0971 1.913 5.57e-02
[sp2] (Intercept) -2.21978 0.2682 -8.277 1.27e-16
[sp2] TrepZ:OCCT 0.66255 0.3093 2.142 3.22e-02
[sp2] TrepZ:OCSS -0.00302 0.1890 -0.016 9.87e-01
AIC: 701.6538
Number of sites: 163
optim convergence code: 0
optim iterations: 48
Bootstrap iterations: 30
range(SC$Dog_Z)
[1] -1.581462 1.158784
> seqD <- seq(-1.581462, 1.158784, length.out=100)
> nd <- data.frame(Dog_Z = seqD)
> predict(y6_3, type = "state", species = "sp1:sp2", newdata = nd)
Error in name_to_ind(species, names(object@data@ylist)) :