Technological modelling for graphical models: an approach based on genetic algorithms

DOI10.1016/j.csda.2003.11.006zbMath1429.62206OpenAlexW2081420753MaRDI QIDQ957013

Sandra Paterlini, Alberto Roverato

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2003.11.006

zbMATH Keywords

genetic algorithmmodel searchscientific modellinglog-linear graphical modeltechnological modelling

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Approximation methods and heuristics in mathematical programming (90C59) Contingency tables (62H17)

Related Items (2)

Applications of optimization heuristics to estimation and modelling problems ⋮ Model-based clustering with sparse covariance matrices

Uses Software

• Matlab
• GAToolBox
• GraphFitI
• MIM

Cites Work

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• Genetic algorithms and their statistical applications: an introduction
• Markov fields and log-linear interaction models for contingency tables
• MCMC model determination for discrete graphical models
• Probabilistic Networks and Expert Systems
• Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
• Introduction to Graphical Modelling
• Stochastic Optimization: A Review
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
• Decomposable graphical Gaussian model determination
• A genetic algorithm for graphical model selection

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