MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions
This paper introduces MoTBFs, an R package for manipulating mixtures of truncated basis functions. This class of functions allows the representation of joint probability distributions involving discrete and continuous variables simultaneously, and includes mixtures of truncated exponentials and mixt...
Asıl Yazarlar: | Maldonado González, Ana Devaki, Salmerón Cerdán, Antonio, Pérez Bernabé, Inmaculada, Nielsen, Thomas Dyhre |
---|---|
Materyal Türü: | info:eu-repo/semantics/article |
Dil: | English |
Baskı/Yayın Bilgisi: |
The R Foundation
2023
|
Online Erişim: | http://hdl.handle.net/10835/14822 |
Benzer Materyaller
-
Mixtures of Truncated Basis Functions
Yazar:: Langseth, Helge, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Learning Mixtures of Truncated Basis Functions from Data
Yazar:: Langseth, Helge, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Learning Conditional Distributions using Mixtures of Truncated Basis Functions
Yazar:: Pérez-Bernabé, Inmaculada, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Learning hybrid Bayesian networks using mixtures of truncated exponentials
Yazar:: Romero, Vanessa, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Structural Learning of Bayesian Networks with Mixtures of Truncated Exponentials
Yazar:: Romero, Vanessa, ve diğerleri
Baskı/Yayın Bilgisi: (2012)