A genetic algorithm for graphical model selection
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Graphical log-linear model search is usually performed by using stepwise procedures in which edges are sequentially added or eliminated from the independence graph. In this paper we implement the search procedure as a genetic algorithm and propose a crossover operator which operates on subgraphs. In a simulation study the proposed procedure is shown to perform better than an automatic backward elimination procedure at the cost of a small increase of computational time.
KeywordsAIC Genetic Algorithm Graphical model Log-linear model Model selection Undirected graph
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