Comparison of Methods for Testing the Hypothesis of Independence of Random Variables Based on a Nonparametric Classifier and Pearson’s Chi-Squared Test

A technique for testing the hypothesis about the independence of random variables, based on a nonparametric pattern recognition algorithm, is used in the analysis of ambiguous dependencies. The pattern recognition algorithm meets the maximum likelihood criterion. The assessment of distribution laws...

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Veröffentlicht in:	Optoelectronics, instrumentation, and data processing Jg. 59; H. 5; S. 551 - 560
Hauptverfasser:	Lapko, A. V., Lapko, V. A., Bakhtina, A. V.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Moscow Pleiades Publishing 01.10.2023
Schlagworte:	Analysis and Synthesis of Signals and Images Lasers Optical Devices Optics Photonics Physics Physics and Astronomy ambiguous functional dependences kernel probability density estimate testing the hypothesis of independence of random variables two-dimensional random variables nonparametric pattern recognition algorithm Pearson’s chi-squared test
ISSN:	8756-6990, 1934-7944
Online-Zugang:	Volltext
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