✦ LIBER ✦

A Bayesian Network Approach for Multivariate Radiation Pneumonitis Modeling

✍ Scribed by Lee, S.; Bradley, J.; Ybarra, N.; Jeyaseelan, K.; Kopek, N.; Seuntjens, J.; El Naqa, I.

Book ID: 122552562
Publisher: Elsevier Science
Year: 2012
Tongue: English
Weight: 56 KB
Volume: 84
Category: Article
ISSN: 0360-3016
DOI: 10.1016/j.ijrobp.2012.07.309

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A hybrid Bayesian back-propagation neura

A hybrid Bayesian back-propagation neural network approach to multivariate modelling

✍ C. G. Chua; A. T. C. Goh 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 253 KB

Bayesian networks for discrete multivari

Bayesian networks for discrete multivariate data: an algebraic approach to inference

✍ J.Q. Smith; J. Croft 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 213 KB

In this paper we demonstrate how Gro¨bner bases and other algebraic techniques can be used to explore the geometry of the probability space of Bayesian networks with hidden variables. These techniques employ a parametrisation of Bayesian network by moments rather than conditional probabilities. We s

A Bayesian coregionalization approach fo

A Bayesian coregionalization approach for multivariate pollutant data

✍ Schmidt, Alexandra M.; Gelfand, Alan E. 📂 Article 📅 2003 🏛 American Geophysical Union 🌐 English ⚖ 261 KB

A Bayesian approach to flexible modeling

A Bayesian approach to flexible modeling of multivariable response functions

✍ David M. Steinberg 📂 Article 📅 1990 🏛 Elsevier Science 🌐 English ⚖ 843 KB

Model of conceptual change for INQPRO: A

Model of conceptual change for INQPRO: A Bayesian Network approach

✍ Ting, Choo-Yee; Sam, Yok-Cheng; Wong, Chee-Onn 📂 Article 📅 2013 🏛 Elsevier Science 🌐 English ⚖ 900 KB

A Bayesian approach to relaxing paramete

A Bayesian approach to relaxing parameter restrictions in multivariate GARCH models

✍ Brent G. Hudson; Richard H. Gerlach 📂 Article 📅 2007 🏛 CrossRef test prefix 🌐 English ⚖ 676 KB

We propose a Bayesian prior formulation for a multivariate GARCH model that expands the allowable parameter space, directly enforcing both necessary and sufficient conditions for positive definiteness and covariance stationarity. This extends the standard approach of enforcing unnecessary parameter