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-rw-r--r--man/gpcount.Rd11
1 files changed, 7 insertions, 4 deletions
diff --git a/man/gpcount.Rd b/man/gpcount.Rd
index f847baa..b7e3b1a 100644
--- a/man/gpcount.Rd
+++ b/man/gpcount.Rd
@@ -10,7 +10,7 @@ population size, availability, and detection probability.
}
\usage{
gpcount(lambdaformula, phiformula, pformula, data,
-mixture = c("P", "NB"), K, starts, method = "BFGS", se = TRUE,
+mixture = c("P", "NB", "ZIP"), K, starts, method = "BFGS", se = TRUE,
engine = c("C", "R"), threads=1, ...)
}
\arguments{
@@ -27,7 +27,8 @@ engine = c("C", "R"), threads=1, ...)
An object of class unmarkedFrameGPC
}
\item{mixture}{
- Either "P" or "NB" for Poisson and negative binomial distributions
+ Either "P", "NB", or "ZIP" for Poisson, negative binomial, or
+ zero-inflated Poisson distributions
}
\item{K}{
The maximum possible value of M, the super-population size.
@@ -58,11 +59,13 @@ engine = c("C", "R"), threads=1, ...)
\details{
The latent transect-level super-population abundance distribution
\eqn{f(M | \mathbf{\theta})}{f(M | theta)} can be set as either a
- Poisson or a negative binomial random variable, depending on the
+ Poisson, negative binomial, or zero-inflated Poisson random variable, depending on the
setting of the \code{mixture} argument. The expected value of
\eqn{M_i} is \eqn{\lambda_i}{lambda_i}. If \eqn{M_i \sim NB}{M_i ~ NB},
then an additional parameter, \eqn{\alpha}{alpha}, describes
- dispersion (lower \eqn{\alpha}{alpha} implies higher variance).
+ dispersion (lower \eqn{\alpha}{alpha} implies higher variance). If
+ \eqn{M_i \sim ZIP}{M_i ~ ZIP}, then an additional zero-inflation parameter
+ \eqn{\psi}{psi} is estimated.
The number of individuals available for detection at time j
is a modeled as binomial: