Computation of Noncentral F Probabilities using multilayer neural network


The KIPS Transactions:PartB , Vol. 9, No. 3, pp. 271-276, Jun. 2002
10.3745/KIPSTB.2002.9.3.271,   PDF Download:

Abstract

The test statistic in ANOVA tests has a single or doubly noncentral F distribution and the noncentral F distribution is applied to the calculation of the power functions of tests of general linear hypotheses. Although various approximations of noncentral F distribution are suggested, they are troublesome to compute. In this paper, the calculation of noncentral F distribution is applied to the neural network theory, to solve the computation problem. The neural network consists of the multi-layer perceptron structure and learning process has the algorithm of the backpropagation. Using Tables and figs, comparisons are made between the results obtained by neural network theory and the Patnaik´s values. Regarding of accuracy and calculation, the results by neural network are efficient than the Patnaik´s values.


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Cite this article
[IEEE Style]
S. H. Gu, "Computation of Noncentral F Probabilities using multilayer neural network," The KIPS Transactions:PartB , vol. 9, no. 3, pp. 271-276, 2002. DOI: 10.3745/KIPSTB.2002.9.3.271.

[ACM Style]
Son Hee Gu. 2002. Computation of Noncentral F Probabilities using multilayer neural network. The KIPS Transactions:PartB , 9, 3, (2002), 271-276. DOI: 10.3745/KIPSTB.2002.9.3.271.