# Simulate faecal egg count data (1-sample situation)

### Description

Simulates (zero-inflated) egg count data

### Usage

1 |

### Arguments

`n` |
sample size (number of faeces collected) |

`mean` |
true number of eggs per gram (epg) |

`kappa` |
overdispersion parameter, |

`phi` |
prevalence i.e. proportion of infected animals, between 0 and 1 |

`f` |
correction factor of the egg counting technique, either an integer or a vector of integers with length |

`rounding` |
logical. If true, the Poisson mean for the raw counts is rounded. The rounding applies since the mean epg is frequently reported as an integer value. For more information, please see Details. |

### Details

The simulation process does not exactly match the proposed models in [ref:paper], however the simulated data resembles the data observed in real world.

In the simulation of raw (`master`

) counts, it follows a Poisson distribution with some mean. The mean is frequently rounded down if it has a very low value and `rounding = TRUE`

, hence there expects to be a negative bias overall when *μ* < 150. Set `rounding = FALSE`

if one does not wish to have any bias in the simulated counts.

### Value

A matrix with three columns, namely the observed epg (`obs`

),
number of eggs counted on the McMaster slide (`master`

) and
true egg counts (`true`

).

### Author(s)

Michaela Paul michaela.paul@uzh.ch

Craig Wang craig.wang@uzh.ch

### See Also

`fec_stan`

for analyzing faecal egg count data with one sample

### Examples

1 |

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