get_posterior_param {dupiR} | R Documentation |
Compute posterior probability distribution parameters (e.g. credible intervals)
for an object of class Counts
Description
This function computes posterior parameters and credible intervals at the given confidence level (default to 95%).
Usage
get_posterior_param(object, low = 0.025, up = 0.975, ...)
Arguments
object |
object of class |
low |
1 - right tail posterior probability |
up |
left tail posterior probability |
... |
additional parameters to be passed to plot_posterior |
Value
an object of class Counts
Author(s)
Federico Comoglio
References
Comoglio F, Fracchia L and Rinaldi M (2013) Bayesian inference from count data using discrete uniform priors. PLoS ONE 8(10): e74388
Clough HE et al. (2005) Quantifying Uncertainty Associated with Microbial Count Data: A Bayesian Approach. Biometrics 61: 610-616
Examples
counts <- new_counts(counts = c(20,30), fractions = c(0.075, 0.10))
# default parameters ("dup" algorithm, sampling without replacement, default prior support)
posterior <- compute_posterior(counts)
get_posterior_param(posterior)
[Package dupiR version 1.2.1 Index]