Bolstad (version 0.2-41)

sd.Bolstad: Posterior standard deviation

Description

Posterior standard deviation

Usage

# S3 method for Bolstad
sd(x, ...)

Arguments

x

an object of class Bolstad for which we want to compute the standard deviation.

…

Any additional arguments to be passed to sd.

Calculate the posterior standard deviation of an object of class Bolstad. If the object has a member sd then it will return this value otherwise it will calculate the posterior standard deviation \(sd[\theta|x]\) using linear interpolation to approximate the density function and numerical integration where \(\theta\) is the variable for which we want to do Bayesian inference, and \(x\) is the data.

Examples

# NOT RUN {
## The usefulness of this method is really highlighted when we have a general 
## continuous prior. In this example we are interested in the posterior
## standard deviation of an normal mean. Our prior is triangular over [-3, 3]
set.seed(123)
x = rnorm(20, -0.5, 1)

mu = seq(-3, 3, by = 0.001)

mu.prior = rep(0, length(mu))
mu.prior[mu <= 0] = 1 / 3 + mu[mu <= 0] / 9
mu.prior[mu > 0] = 1 / 3 - mu[mu > 0] / 9

results = normgcp(x, 1, density = "user", mu = mu, mu.prior = mu.prior, plot = FALSE)
sd(results)
# }