lestat-package {lestat}

LEarning STATistics using Bayesian object oriented computation

Description

The package contains a number of simple functions which can be combined to implement simple Bayesian computations.

Details

Package:	lestat
Type:	Package
Version:	1.6
Date:	2011-12-15
License:	GPL-2
LazyLoad:	yes

With this package, functions can be used to create objects representing probability distributions of many different types. These distributions can then be transformed and combined in different ways, representing statistical modelling. The result is an object-oriented way to do Bayesian computation with R.

Author(s)

Petter Mostad <[e-mail]>

References

Please see more information at www.math.chalmers.se/~mostad/

Examples

prior <- normalexpgamma() #Generate a two-parameter flat prior
full <- linearpredict(prior, rep(1, 7)) #Extend with normal distribution
data <- runif(7) #Generate data
posterior <- conditional(full, 1:7, data) #Condition on parameters
credibilityinterval(marginal(posterior, 1)) #Investigate posterior