blmeco (version 1.4)

triplot.normal.knownvariance: Draw prior, data and posterior for a known variance normal distribution example

Description

The function draws a normal prior distribution, the data and the posterior distribution in one plot. It serves as a tool to explore the influence of different prior on a hypotehtical set of normally distributed data

Usage

triplot.normal.knownvariance(theta.data, variance.known, n, prior.theta, prior.variance, 
legend = TRUE, ylim = c(0, max(yposterior)), legend.bty="n")

Arguments

theta.data

mean of the data

variance.known

known variance

n

sample size

prior.theta

mean of the prior distribution

prior.variance

variance of the prior distribution

legend

logical, if TRUE (default) a legend is drawn

ylim

ylim of the plot

legend.bty

box type of legend

References

Gelman, A., J. B. Carlin, H. S. Stern and D. B. Rubin (2004). Bayesian Data Analysis. New York, Chapman & Hall/CRC.

See Also

dnorm

Examples

# NOT RUN {
triplot.normal.knownvariance(theta.data=10, n=20, variance.known=5, 
   prior.theta=0, prior.variance=100) 
# }