𝔖 Scriptorium
✦   LIBER   ✦
📁

Graphical models with R

✍ Scribed by Edwards, David;Højsgaard, Søren;Lauritzen, Steffen L

Publisher
Springer
Year
2012
Tongue
English
Leaves
187
Series
Use R!
Category
Library
⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Table of Contents

Graphs and Conditional Independence.- Log-Linear Models.- Bayesian Networks.- Gaussian Graphical Models.- Mixed Interaction Models.- Graphical Models for Complex Stochastic Systems.- High dimensional modelling.- References.- Index.

✦ Subjects

statistika;R (Computer program language);Graphical modeling (Statistics);statistika -- statistične metode -- grafično modeliranje -- računalništvo -- programiranje -- programski jezik R

📜 SIMILAR VOLUMES

Graphical Models with R
📁 Graphical Models with R
✍ Søren Højsgaard, David Edwards, Steffen Lauritzen (auth.) 📂 Library 📅 2012 🏛 Springer-Verlag New York 🌐 English

<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
📁 Graphical Models with R
✍ Søren Højsgaard, David Edwards, Steffen Lauritzen (auth.) 📂 Library 📅 2012 🏛 Springer-Verlag New York 🌐 English

<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
📁 Graphical Models with R
✍ Søren Højsgaard, David Edwards, Steffen Lauritzen (auth.) 📂 Library 📅 2012 🏛 Springer 🌐 English
Graphical Models with R (Use R!)
📁 Graphical Models with R (Use R!)
✍ Søren Højsgaard 📂 Library 📅 2012 🏛 Springer 🌐 English

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.

Graphical Models with R (Use R!)
📁 Graphical Models with R (Use R!)
✍ Søren Højsgaard 📂 Library 📅 2012 🏛 Springer 🌐 English

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.

Learning Probabilistic Graphical Models
📁 Learning Probabilistic Graphical Models in R: Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R
✍ David Bellot 📂 Library 📅 2016 🏛 Packt Publishing 🌐 English

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