In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.
We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.
In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.
We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.
GRAPH CREATION
Using our fast, responsive interactive user interface, your can create your own graphs. You have the ability to sample and analyse on the fly or save them for later use.
Features

Add/remove nodes, edges.

Edit names of nodes and edges.

Drag and drop functionality

Different node shapes based on node type

Download and Upload graphs

Simple JSON representation

Editable Conditional Probability Distributions

Trigger sampling and scenario analysis

Zooming, moving and bulk selection

Undo graph changes