posterior: Posterior distribution

In bayesdistreg: Bayesian Distribution Regression

Description

posterior computes the value of the posterior at parameter values pars

Usage

posterior(pars, data, Log = TRUE, mu = 0, sig = 25,
  prior = "Normal")

Arguments

pars	parameter values
data	dataframe. The first column must be the binary dependent variable
Log	logical to take the log of the posterior.(defaults to TRUE)
mu	mean of prior of each parameter value in case the prior is Normal (default: 0)
sig	standard deviation of prior of each parameter in case the prior is Normal (default: 25)
prior	string input of "Normal" or "Uniform" prior distribution to use

Value

val value function of the posterior

Examples

y = indicat(faithful$waiting,mean(faithful$waiting)) 
x = scale(cbind(faithful$eruptions,faithful$eruptions^2))
data = data.frame(y,x)
posterior(rep(0,3),data,Log = FALSE,mu=0,sig = 10,prior = "Normal") # no log
posterior(rep(0,3),data,Log = TRUE,mu=0,sig = 10,prior = "Normal") # log
posterior(rep(0,3),data,Log = TRUE) # use default values

bayesdistreg documentation built on May 1, 2019, 8:03 p.m.