secr (version 2.4.0)

pdot: Net Detection Probability

Description

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

Usage

pdot(X, traps, detectfn = 0, detectpar = list(g0 = 0.2,
    sigma = 25, z = 1), noccasions = 5, binomN = NULL)

Arguments

X

vector or 2-column matrix of coordinates

traps

traps object

detectfn

integer code for detection function q.v.

detectpar

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

noccasions

number of intervals (occasions)

binomN

integer code for discrete distribution (see secr.fit)

Value

• A vector of probabilities, one for each row in X.

Details

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. 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.

See Also

secr, make.mask, detection functions, pdot.contour

Examples

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))