GENCAPH1 - Generate Capture Histories
No User-Manual has been written for GENCAPH1 (yet). Here is a
short description:
This program generates capture-histories of a virtual population
of animals with given survival and capture probabilities.
Output from this program includes all observable capture-histories,
along with the number of animals which exhibited each history.
This output may be used as input to other programs (like MARK, CAPTURE, JOLLY)
to compute estimates of survival, capture probabilities, or
population size.
Uses of this program include:
- Calculate bias in estimated parameters for incorrectly specified models,
- Calculate confidence-interval coverage,
- Compute model goodness-of-fit
Here's how it works:
The expected numbers of animals exhibiting each capture
history are computed using a recursive algorithm
coded in C. The algorithm follows a population of animals, exposing them to
capture and survival until death or the end of the study, while saving a
vector of codes (0=not captured, 1=captured) indicating capture history. The
process is repeated for each cohort of injected animals in capture occasions
after the first.
There are two modes of operation of the program - Deterministic and Stochastic.
Under Deterministic mode, the number of animals is retained throughout the process
as a fractional number and is multiplied by the parameters to get the final number
of animals with each capture-history. This results in two things: capture-history
frequencies are not integers, and parameter estimates will match input parameters
exactly (almost). In Stochastic mode, the number of animals is achieved via
a simulation function (binomial) on the parameters. In this mode, the number of
animals with each capture-history will be integers, and the data (and resulting
estimates) will be different for each program run.
Terminology and Notation for Input Data
- N(i) = Number of new animals introduced into the population just before time i
- phi(i) = survival rate from time i to i+1,
- theta(i) = tag-retention rate from age or time i to i+1
- p(i) = capture probability for unmarked animals in time i
- c(i) = capture probability for marked animals in time i
- f(i) = number of new individuals in time i per old individual in time i-1