lbinorm

Computes the logarithm of a bivariate normal density

models

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

lbinorm function

<dl> <dt>xy</dt>
<dd>vector of values of two variables x and y</dd> <dt>par</dt>
<dd>list with components m, a vector of means, and v, a variance-covariance matrix</dd></dl>

Arguments

Author

Logarithm of bivariate normal density — lbinorm

<dl>

 <dt>xy</dt>
<dd>vector of values of two variables x and y</dd>

 <dt>par</dt>
<dd>list with components m, a vector of means, and v, a variance-covariance matrix</dd>

</dl>

lbinorm: Logarithm of bivariate normal density

Description

Usage

Value

Arguments

Author

Examples