nvaricp {Bolstad} | R Documentation |
Evaluates and plots the posterior density for sigma, the standard deviation of a Normal distribution where the mean mu is known
nvaricp(y, mu, S0, kappa, ...)
y |
a random sample from a normal(mu,sigma^2) distribution. |
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 |
A list will be returned with the following components:
sigma |
the vaules of sigma for which the prior, likelihood and posterior have been calculated |
prior |
the prior density for sigma |
likelihood |
the likelihood function for sigma given y |
posterior |
the posterior density of sigma given y |
S1 |
the posterior scaling constant |
kappa1 |
the posterior degrees of freedom |
## 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))