herd_summary: Summary of herd level probabilities of infection generated by...

In AurMad/STOCfree: STOC free model: prediction of probability of freedom from longitudinal data

Summary of herd level probabilities of infection generated by the STOC free model

Description

Summary of herd level probabilities of infection generated by the STOC free model

Usage

herd_summary(x = data.frame(), quantile = 0.5, cut_off = 0.5)

Arguments

x	a data frame with MCMC samples for the herd level probabilities of being latent status positive
quantile	use to summarise each herd's MCMC samples
cut_off	cut-off value used to categorise herds as negative or positive

Value

for each herd, the quantile supplied is computed from the MCMC samples for the predicted probabilities of infection. So, if a value of 0.5 is supplied for quantile, the median probability of infection is computed. The cut_off argument is then used to categorise each herd as status positive or status negative.

AurMad/STOCfree documentation built on Sept. 13, 2022, 3:20 a.m.