pdot: Net Detection Probability

Description Usage Arguments Details Value Note See Also Examples

Description

Compute spatially explicit net probability of detection for individual(s) at given coordinates.

Usage

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pdot(X, traps, detectfn = 0, detectpar = list(g0 = 0.2,
    sigma = 25, z = 1), noccasions = NULL, binomN = NULL,
    userdist = NULL, ncores = NULL) 
    
CVpdot(..., conditional = FALSE)    

Arguments

X

vector or 2-column matrix of coordinates

traps

traps object

detectfn

integer code for detection function q.v.

detectpar

a named list giving a value for each parameter of detection function

noccasions

number of sampling intervals (occasions)

binomN

integer code for discrete distribution (see secr.fit)

userdist

user-defined distance function or matrix (see userdist)

ncores

integer number of threads

...

arguments passed to pdot

conditional

logical; if TRUE then computed mean and CV are conditional on detection

Details

If traps has a usage attribute then noccasions is set accordingly; otherwise it must be provided.

The probability computed is p.(X) = 1 - (1 - prod(p_s(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.

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.(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.

Value

For pdot, a vector of probabilities, one for each row in X.

For CVpdot, a named vector with elements ‘meanpdot’ and ‘CVpdot’.

Note

CVpdot computes the mean μ and variance V of the location-specific overall detection probability p.(X) as follows.

μ = \int p.(X) f(X) dX,

V = \int p.(X)^2 f(X) dX - μ^2.

For uniform density and conditional = FALSE, f(X) is merely a scaling factor independent of X.

If conditional = TRUE then f(X) = p.(X) / \int p.(X) dX.

The coefficient of variation is CV = sqrt(V)/μ.

See Also

secr, make.mask, Detection functions, pdot.contour, CV

Examples

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## Not run: 

  temptrap <- make.grid()
  ## per-session detection probability for an individual centred
  ## at a corner trap. By default, noccasions = 5.
  pdot (c(0,0), temptrap, detectpar = list(g0 = 0.2, sigma = 25),
    noccasions = 5)
    
  msk <- make.mask(temptrap, buffer = 100)
  CVpdot(msk, temptrap, detectpar = list(g0 = 0.2, sigma = 25),
    noccasions = 5)

## End(Not run)

secr documentation built on Oct. 18, 2021, 9:06 a.m.