capture {repeated} R Documentation

## Capture-recapture Models

### Description

`capture` fits the Cormack capture-recapture model to `n` sample periods. Set `n` to the appropriate value and type `eval(setup)`.

`n <- periods` # number of periods

`eval(setup)`

This produces the following variables -

`p[i]`: logit capture probabilities,

`pbd`: constant capture probability,

`d[i]`: death parameters,

`b[i]`: birth parameters,

`pw`: prior weights.

Then set up a Poisson model for log linear models:

`z <- glm(y~model, family=poisson, weights=pw)`

and call the function, `capture`.

If there is constant effort, then all estimates are correct. Otherwise, `n[1]`, `p[1]`, `b[1]`, are correct only if there is no birth in period 1. `n[s]`, `p[s]`, are correct only if there is no death in the last period. `phi[s-1]` is correct only if effort is constant in `(s-1, s)`. `b[s-1]` is correct only if `n[s]` and `phi[s-1]` both are.

### Usage

```capture(z, n)
```

### Arguments

 `z` A Poisson generalized linear model object. `n` The number of repeated observations.

### Value

`capture` returns a matrix containing the estimates.

J.K. Lindsey

### Examples

```y <- c(0,1,0,0,0,1,0,1,0,0,0,1,0,0,0,14,1,1,0,2,1,2,1,16,0,2,0,11,
2,13,10,0)
n <- 5
eval(setup)
# closed population
print(z0 <- glm(y~p1+p2+p3+p4+p5, family=poisson, weights=pw))
# deaths and emigration only
print(z1 <- update(z0, .~.+d1+d2+d3))
# immigration only
print(z2 <- update(z1, .~.-d1-d2-d3+b2+b3+b4))
# deaths, emigration, and immigration
print(z3 <- update(z2, .~.+d1+d2+d3))