Markov chain Monte Carlo methods for the regular two-level fractional factorial designs and cut ideals

DOI10.1016/j.jspi.2013.06.009zbMath1279.62159arXiv1302.2882OpenAlexW2963729569MaRDI QIDQ394788

Hidefumi Ohsugi, Satoshi Aoki, Takayuki Hibi

Publication date: 27 January 2014

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1302.2882

zbMATH Keywords

design of experimentsMarkov basiscondional testscut ideals

Mathematics Subject Classification ID

Applications of graph theory (05C90) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40) Factorial statistical designs (62K15) Markov processes (60J99)

Related Items (1)

Markov-chain Monte Carlo methods for the Box-Behnken designs and centrally symmetric configurations

Uses Software

• 4ti2

Cites Work

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• Markov bases in algebraic statistics.
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• Toric geometry of cuts and splits
• Properties of cut ideals associated to ring graphs
• Markov bases of binary graph models of \(K_{4}\)-minor free graphs
• Markov chain Monte Carlo tests for designed experiments
• Confounding revisited with commutative computational algebra
• Markov bases for decomposable graphical models
• Classification of two-level factorial fractions
• Algebraic algorithms for sampling from conditional distributions
• Generalised confounding with Grobner bases
• Extremal graphs without three‐cycles or four‐cycles
• Monte Carlo sampling methods using Markov chains and their applications

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