# Fake data
R <- 4 # number of sites
J <- 3 # number of visits
y <- matrix(c(
1,2,0,
0,0,0,
1,1,1,
2,2,1), nrow=R, ncol=J, byrow=TRUE)
y
site.covs <- data.frame(x1=1:4, x2=factor(c('A','B','A','B')))
site.covs
obs.covs <- list(
x3 = matrix(c(
-1,0,1,
-2,0,0,
-3,1,0,
0,0,0), nrow=R, ncol=J, byrow=TRUE),
x4 = matrix(c(
'a','b','c',
'd','b','a',
'a','a','c',
'a','b','a'), nrow=R, ncol=J, byrow=TRUE))
obs.covs
umf <- unmarkedFramePCount(y=y, siteCovs=site.covs,
obsCovs=obs.covs) # organize data
umf # take a l
summary(umf) # summarize data
fm <- pcount(~1 ~1, umf, K=10) # fit a model
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