Open AccessModel specification search using a genetic algorithm with factor reordering for a simple structure factor analysis model
Author(s) -
MUROHASHI HIROTO,
TOYODA HIDEKI
Publication year - 2007
Publication title -
japanese psychological research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.392
H-Index - 30
eISSN - 1468-5884
pISSN - 0021-5368
DOI - 10.1111/j.1468-5884.2007.00345.x
Subject(s) - factor (programming language) , simple (philosophy) , computer science , algorithm , metaheuristic , genetic algorithm , focus (optics) , data mining , machine learning , philosophy , physics , epistemology , optics , programming language
Many techniques for automated model specification search based on numerical indices have been proposed, but no single decisive method has yet been determined. In the present article, the performance and features of the model specification search method using a genetic algorithm (GA) were verified. A GA is a robust and simple metaheuristic algorithm with great searching power. While there has already been some research applying metaheuristics to the model fitting task, we focus here on the search for a simple structure factor analysis model and propose a customized algorithm for dealing with certain problems specific to that situation. First, implementation of model specification search using a GA with factor reordering for a simple structure factor analysis is proposed. Then, through a simulation study using generated data with a known true structure and through example analysis using real data, the effectiveness and applicability of the proposed method were demonstrated.