unmarkedFrameOccuFP.RdOrganizes detection, non-detection data along with the covariates.
This S4 class is required by the data argument of occu and
occuRN
unmarkedFrameOccuFP(y, siteCovs=NULL, obsCovs=NULL, type, mapInfo)An RxJ matrix of the detection, non-detection data, where R is the number of sites, J is the maximum number of sampling periods per site.
A data.frame of covariates that vary at the
site level. This should have M rows and one column per covariate
Either a named list of data.frames of
covariates that vary within sites, or a data.frame with
RxJ rows in site-major order.
A vector with 3 values designating the number of occassions
where data is of type 1, type 2, and type 3 - see occuFP
for more details about data types.
Currently ignored
unmarkedFrameOccuFP is the S4 class that holds data to be passed
to the occu and occuRN model-fitting function.
an object of class unmarkedFrameOccuFP
n = 100
o = 10
o1 = 5
y = matrix(0,n,o)
p = .7
r = .5
fp = 0.05
y[1:(n*.5),(o-o1+1):o] <- rbinom((n*o1*.5),1,p)
y[1:(n*.5),1:(o-o1)] <- rbinom((o-o1)*n*.5,1,r)
y[(n*.5+1):n,(o-o1+1):o] <- rbinom((n*o1*.5),1,fp)
type <- c((o-o1),o1,0) ### vector with the number of each data type
site <- c(rep(1,n*.5*.8),rep(0,n*.5*.2),rep(1,n*.5*.2),rep(0,n*.8*.5))
occ <- matrix(c(rep(0,n*(o-o1)),rep(1,n*o1)),n,o)
site <- data.frame(habitat = site)
occ <- list(METH = occ)
umf1 <- unmarkedFrameOccuFP(y,site,occ, type = type)
m1 <- occuFP(detformula = ~ METH, FPformula = ~1, stateformula = ~ habitat, data = umf1)