Stable Specification Search in Structural Equation Models

An exploratory and heuristic approach for specification search in Structural Equation Modeling. The basic idea is to subsample the original data and then search for optimal models on each subset. Optimality is defined through two objectives: model fit and parsimony. As these objectives are conflicting, we apply a multi-objective optimization methods, specifically NSGA-II, to obtain optimal models for the whole range of model complexities. From these optimal models, we consider only the relevant model specifications (structures), i.e., those that are both stable (occur frequently) and parsimonious and use those to infer a causal model.


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0.3.0 by Ridho Rahmadi, 4 years ago

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Authors: Ridho Rahmadi [aut, cre] , Perry Groot [aut, ths] , Tom Heskes [aut, ths] , Christoph Stich [ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports ggm, matrixcalc, sem, nsga2R, graph, Rgraphviz, methods, polycor, foreach

Suggests testthat

See at CRAN