gamma_poisson_clough: Compute posterior probability using a Gamma-Poisson model...

In dupiR: Bayesian Inference from Count Data using Discrete Uniform Priors

Compute posterior probability using a Gamma-Poisson model (Clough et al.)

Description

Compute posterior probability using a Gamma-Poisson model (Clough et al.)

Usage

gamma_poisson_clough(object, n_start, n_end, a = 1, b = 1e-10)

Arguments

object	object of class Counts
n_start	start of prior support range
n_end	end of prior support range
a	prior shape parameter of the gamma distribution used to compute the posterior with Clough. Default to 1
b	prior rate parameter of the gamma distribution used to compute the posterior with Clough. Default to 1e-10

Value

vector of posterior probabilities

Note

if support range spans more than 100k values, the posterior is not computed

dupiR documentation built on May 29, 2024, 1:21 a.m.