BIFROST -- Block recursive models Induced From Relevant knowledge, Observations, and Statistical Techniques

DOI10.1016/0167-9473(93)E0054-8zbMath0875.62566OpenAlexW1996601454MaRDI QIDQ674208

Bo Thiesson, Søren Højsgaard

Publication date: 28 February 1997

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

Full work available at URL: https://doi.org/10.1016/0167-9473(93)e0054-8

zbMATH Keywords

Model selectionMachine learningCausal probabilistic networksGraphical association modelsSelection criteriaSelection strategies

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics (62P99) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items

Learning structures from data and experts, Bayesian learning of Bayesian networks with informative priors, Split models for contingency tables, Enumerating the decomposable neighbors of a decomposable graph under a simple perturbation scheme, Estimation of graphical models whose conditional independence graphs are interval graphs and its application to modelling linkage disequilibrium, Characterizing Markov equivalence classes for AMP chain graph models, Computational learning of the conditional phase-type (C-Ph) distribution. Learning C-Ph distributions, A graphical characterization of the largest chain graphs, Bayesian model averaging and model selection for markov equivalence classes of acyclic digraphs, Separation and completeness properties for AMP chain graph Markov models.

Uses Software

• AS 159

Cites Work

• Algorithm AS 159: An Efficient Method of Generating Random R × C Tables with Given Row and Column Totals
• Graphical models for associations between variables, some of which are qualitative and some quantitative
• Markov fields and log-linear interaction models for contingency tables
• Estimating the dimension of a model
• Marginalization and collapsibility in graphical interaction models
• Graphical and Recursive Models for Contingency Tables
• A fast procedure for model search in multidimensional contingency tables
• A Fast Model Selection Procedure for Large Families of Models
• Decomposition of maximum likelihood in mixed graphical interaction models
• Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models
• Model Search among Multiplicative Models
• Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
• Independence properties of directed markov fields
• Simultaneous Test Procedures--Some Theory of Multiple Comparisons
• The Analysis of Multidimensional Contingency Tables: Stepwise Procedures and Direct Estimation Methods for Building Models for Multiple Classifications
• A new look at the statistical model identification
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item