# pdot: Net Detection Probability In secr: Spatially Explicit Capture-Recapture

## Description

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

## Usage

 ```1 2 3``` ```pdot(X, traps, detectfn = 0, detectpar = list(g0 = 0.2, sigma = 25, z = 1), noccasions = NULL, binomN = NULL, userdist = NULL) ```

## 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)

## 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.

## Value

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

`secr`, `make.mask`, `Detection functions`, `pdot.contour`
 ```1 2 3 4 5``` ``` 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) ```