Gibbs sampling in Analytica

This page is a knowledge crystal of subtype method. The page identifier is Op_en2670
Moderator:Nobody (see all) Click here to sign up.

Upload data {{#opasnet_base_link:Op_en2670}}

Scope

What is a good way to perform Gibbs sampling in Analytica such that

it is easy to operationalise Bayesian updating within a model.

Definition

Input

The input should contain data and likelihood and prior distributions. This should be able to build for several model nodes, as they may serve as data for each other.

Output

The output should contain a posterior distribution.

Rationale

A tricky question is, what to do with probabilistic nodes, as in Analytica the default is that nodes are functional nodes. Can the definition of a node be described probabilistically?

Result

Procedure

Gibbs sampler should be some kind of function. It should have a variable list and a likelihood list as input parameters.