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Written by LEV V. UTKIN, and FRANK P.A. COOLEN   

On Reliability Growth Models Using Kolmogorov-Smirnov Bounds

Volume 7, Number 1, January 2011 - Paper 1 - pp. 5-19

LEV V. UTKIN1, and FRANK P.A. COOLEN2

1 Department of Computer Science, St. Petersburg State Forest Technical Academy
   Institutsky per. 5, 194021 St. Petersburg, Russia
2  Department of Mathematical Sciences, Durham University
   Durham, DH1 3LE, England

(Received on March 16, 2009, revised on June 22, 2010)


Abstract:

An approach for constructing nonparametric imprecise growth models (regression models) is proposed. The approach is based on applying sets of probability distributions of the "noise" produced by means of Kolmogorov-Smirnov bounds. The corresponding growth models are constructed by minimizing the risk functional in the framework of predictive learning and by choosing "optimal" probability distribuions of the "noise" defining the minimax and minimin strategies. Numerical examples illustrate the proposed approach.

 

References: 16

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