If traps
has a usage attribute then noccasions
is
set accordingly; otherwise it must be provided.
The probability computed is \(p.(\mathbf{X}) = 1 - \prod\limits _{k}
\{1 - p_s(\mathbf{X},k)\}^{S}\) where
the product is over the detectors in traps
, excluding any not
used on a particular occasion. The per-occasion detection function
\(p_s\) is halfnormal (0) by default, and is assumed not to vary
over the \(S\) occasions.
From 4.6.11, the detection parameters g0, lambda0 and sigma for point detectors
may be detector- and occasion-specific. This is achieved by providing a vector
of values that is replicated internally to fill a matrix with dimensions
ntraps x noccasions (i.e. in trap order for occasion 1, then occasion 2 etc.)
For detection functions (10) and (11) the signal threshold `cutval' should be
included in detectpar
, e.g., detectpar = list(beta0 = 103, beta1
= -0.11, sdS = 2, cutval = 52.5)
.
The calculation is not valid for single-catch traps because
\(p.(\mathbf{X})\) is reduced by competition between animals.
userdist
cannot be set if `traps' is any of polygon, polygonX,
transect or transectX. if userdist
is a function requiring
covariates or values of parameters `D' or `noneuc' then X
must
have a covariates attribute with the required columns.
Setting ncores = NULL
uses the existing value from the environment variable
RCPP_PARALLEL_NUM_THREADS (see setNumThreads
).
CVpdot
returns the expected mean and CV of pdot across the points listed in X
, assuming uniform population density. X
is usually a habitat mask. See Notes for details.