simulate.posterior: Simulate values from a posterior object

In bayesball/LearnBayes: Learning Bayesian Inference

Description

simulate.posterior will simulate draws from a posterior density.

Usage

## S3 method for class 'posterior'
simulate(object, nsim=1000, seed=NULL, ...)

Arguments

object	posterior object
nsim	number of simulate iterates
seed	starting seed of random number generator
...	optional arguments; use exact=TRUE to simulate from the exact posterior density and the scale argument indicates the scale value for the Metropolis random walk algorithm

Value

sample	matrix of simulated draws of posterior
arate	acceptance rate if the Metropolis random walk algorithm is used

Author(s)

Jim Albert

Examples

data <- c(2,4,3,6,1,0,4,3,10,2)
par <- c(0,1)
datapar <- list(data=data,par=par)
fit <- laplace(logpoissnormal, 1, datapar)
simulate(fit, exact=TRUE, scale=4)

bayesball/LearnBayes documentation built on May 11, 2019, 9:21 p.m.