simData1s: Simulate faecal egg count data (1-sample situation)

In eggCounts: Hierarchical Modelling of Faecal Egg Counts

Simulate faecal egg count data (1-sample situation)

Description

Simulates (zero-inflated) egg count data

Usage

simData1s(n = 10, mean = 500, kappa = 0.5, phi = 1, 
  f = 50, rounding = TRUE, seed = NULL)

Arguments

n	positive integer. Sample size.
mean	numeric. True number of eggs per gram (epg).
kappa	numeric. Overdispersion parameter, \kappa \to \infty corresponds to Poisson distribution.
phi	numeric. Prevalence, i.e. proportion of infected animals, between 0 and 1.
f	positive integer. Correction factor of the egg counting technique, either an integer or a vector of integers with length n.
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, see Details.
seed	integer. Random seed.

Details

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 bias overall when \mu < 150. Set rounding = FALSE for not to have any bias in the simulated counts.

Value

A data.frame with three columns, namely the observed epg (obs), actual number of eggs counted (master) and true epg in the sample (true).

Author(s)

Craig Wang
Michaela Paul

See Also

fec_stan for analyzing faecal egg count data with one sample

Examples

fec <- simData1s(n = 10, mean = 500, 
          kappa = 0.5, phi = 0.7)

eggCounts documentation built on Oct. 15, 2023, 1:06 a.m.