<p><p>Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences. Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years. In recent years many
Graphical Models with R
✍ Scribed by Søren Højsgaard, David Edwards, Steffen Lauritzen (auth.)
- Publisher
- Springer
- Year
- 2012
- Tongue
- English
- Leaves
- 182
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
✦ Subjects
Statistics, general
📜 SIMILAR VOLUMES
<p><p>Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences. Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years. In recent years many
This book offers an introduction to graphical modeling using R and the main features of some of these packages. It provides examples of how more advanced aspects of graphical modeling can be represented and handled within R.
This book offers an introduction to graphical modeling using R and the main features of some of these packages. It provides examples of how more advanced aspects of graphical modeling can be represented and handled within R.
Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov network