nvaricp {Bolstad}  R Documentation 
Bayesian inference for a normal standard deviation with a scaled inverse chisquared distribution
Description
Evaluates and plots the posterior density for \sigma
, the
standard deviation of a Normal distribution where the mean \mu
is
known
Usage
nvaricp(y, mu, S0, kappa, ...)
Arguments
y 
a random sample from a

mu 
the known population mean of the random sample. 
S0 
the prior scaling factor. 
kappa 
the degrees of freedom of the prior. 
... 
additional arguments that are passed to 
Value
A list will be returned with the following components:
sigma 
the vaules of 
prior 
the prior
density for 
likelihood 
the likelihood function
for 
posterior 
the posterior
density of 
S1 
the posterior scaling constant 
kappa1 
the posterior degrees of freedom 
Examples
## Suppose we have five observations from a normal(mu, sigma^2)
## distribution mu = 200 which are 206.4, 197.4, 212.7, 208.5.
y = c(206.4, 197.4, 212.7, 208.5, 203.4)
## We wish to choose a prior that has a median of 8. This happens when
## S0 = 29.11 and kappa = 1
nvaricp(y,200,29.11,1)
## Same as the previous example but a calculate a 95% credible
## interval for sigma. NOTE this method has changed
results = nvaricp(y,200,29.11,1)
quantile(results, probs = c(0.025, 0.975))
[Package Bolstad version 0.241 Index]