bayesgct: Fitting Gamma-Count Model Based on MCMC

In jreduardo/bayescm: Bayesian Inference for Flexible Count Models

Description

Build matrices and organize data to use jags.model andcoda.samples for analysis of Bayesian models using Markov Chain Monte Carlo (MCMC).

Usage

bayesgct(formula, data, .control_model = control_model(),
  .control_samples = control_samples())

Arguments

formula	A formula to define fixed effects.
data	The data frame.
.control_model	See control_model.
.control_samples	See control_samples.

Author(s)

Eduardo Jr

Examples

# Simulate data
beta <- c(3, -1)
X <- cbind(1, runif(50))
y <- rpois(50, lambda = exp(X %*% beta))

# Sampling and summarise posterior
model <- bayesgct(y ~ X - 1)
vapply(model$samples, function(x) apply(x, 2L, mean), double(3))

jreduardo/bayescm documentation built on May 17, 2019, 7:29 p.m.