Description Usage Arguments Value Author(s) References Examples

Simulates count survey data assuming a binomial, normal, or Poisson sampling process. For the last two, it is assumed that individuals may be double counted and missed at the same rate.

1 2 3 | ```
simCountBin(N, pDetect)
simCountNorm(N, sigma)
simCountPois(N)
``` |

`N` |
annual number of individuals at risk of detection, which may be all adults or just those breeding. The length of the vector determines the number of sampling occasions. |

`pDetect` |
vector with the annual detection probabilities of the individuals at risk of counting; all individuals have the same probability to be counted; a scalar can be used if probability does not change with time. |

`sigma` |
vector with the annual observation error (SD); a scalar can be used if error does not change with time. |

A list with the parameters entered and `count`

with the number of individuals counted in each year.

Michael Schaub

Schaub, M., Kéry, M. (2022) *Integrated Population Models*, Academic Press, section 5.5.1.

1 2 3 4 5 6 7 | ```
# Generate a simulated population:
pop <- simPop()
pop$breeders
# Simulate count data of breeders or of adults
simCountBin(pop$totBreeders, p=0.6)
simCountNorm(pop$totBreeders, sigma=10)
simCountPois(pop$totAdults)
``` |

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