# Parametric Bootstrap ECM and TIRM Models

### Description

Uses maximum likelihood parameter estimates from `fitEcm`

, `fitTirm`

, or `fitTirmPartition`

to perform a parametric bootstrap to get confidence intervals for the estimate of the population size

### Usage

1 | ```
bootstrapCapwire(x, bootstraps = 1000, CI = c(0.025, 0.975))
``` |

### Arguments

`x` |
An object inherited from |

`bootstraps` |
The number of bootstraps to be performed (default is 1000) |

`CI` |
A vector of quantiles to to generate a confidence interval for the population estimate. The default is |

### Details

This function uses the ML estimates obtained from fitting the model to simulate data under the model.

`bootstrapCapwire`

inherits an object from `fitEcm`

, `fitTirm`

, or `fitTirmPartition`

such that the model and parameter estimates do not need to be specified.

The ML estimate for the population size will also be returned but this will not be changed by `bootstrapCapwire`

Note that if the model is a poor fit to the data, the confidence intervals may not be reliable.

The lower confidence interval is bounded by the number of unique individuals in the sample.

### Value

`ml.pop.size` |
The maximum likelihood estimate for the population size obtained by fitting the model |

`conf.int` |
The confidence interval for the estimate of the population size |

### Author(s)

Matthew W. Pennell

### References

Miller C. R., P. Joyce and L.P. Waits. 2005. A new method for estimating the size of small populations from genetic mark-recapture data. Molecular Ecology 14:1991-2005.

### See Also

`fitEcm`

, `fitTirm`

, `fitTirmPartition`

### Examples

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