pdot.dsr.integrate.logistic: Compute probability that a object was detected by at least...

In mrds: Mark-Recapture Distance Sampling

Compute probability that a object was detected by at least one observer

Description

Computes probability that a object was detected by at least one observer (pdot or p_.) for a logistic detection function that contains distance.

Usage

pdot.dsr.integrate.logistic(
  right,
  width,
  beta,
  x,
  integral.numeric,
  BT,
  models,
  GAM = FALSE,
  rem = FALSE,
  point = FALSE
)

Arguments

right	either an integration range for binned data (vector of 2) or the rightmost value for integration (from 0 to right)
width	transect width
beta	parameters of logistic detection function
x	data matrix
integral.numeric	set to TRUE unless data are binned (done in this fct) or the model is such that distance is not linear (eg distance^2), If integral.numeric is FALSE it will compute the integral analytically. It should only be FALSE if is.linear.logistic function is TRUE.
BT	FALSE except for the trial configuration; BT stands for Buckland-Turnock who initially proposed a trial configuration for dual observers
models	list of models including g0model
GAM	Not used at present. The idea was to be able to use a GAM for g(0) portion of detection function; should always be F
rem	only TRUE for the removal configuration but not used and could be removed if pulled from the function calls. Originally thought the pdot integral would differ but it is the same as the io formula. The only thing that differs with removal is that p(2|1)=1. Observer 2 sees everything seen by observer 1,
point	TRUE for point transects

Author(s)

Jeff Laake

mrds documentation built on July 9, 2023, 6:06 p.m.