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2016•Optoelectronics Instrumentation and Data ProcessingRequires access

Goodness-of-fit test based on the interval estimation

Evgeny L. Kuleshov

Open publisher page 4 citations

Abstract

A new goodness-of-fit test constructed with the use of the interval estimation of the probability distribution function is proposed. A comparative analysis of this test with the Kolmogorov test is carried out. It is shown that it is possible to select the correct distribution function and the hypothetical function different from it so that the proposed goodness-of-fit test can have a significantly better performance than the Kolmogorov test. The presented numerical simulation results are in good agreement with the theoretical conclusions.

About this research paper

What this paper is about

A new goodness-of-fit test constructed with the use of the interval estimation of the probability distribution function is proposed. A comparative analysis of this test with the Kolmogorov test is carried out. It is shown that it is possible to select the correct distribution function and the hypothetical function different from it so that the proposed goodness-of-fit test can have a significantly better performance than the Kolmogorov test. The presented numerical simulation results are in good agreement with the theoretical conclusions.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A new goodness-of-fit test constructed with the use of the interval estimation of the probability distribution function is proposed. A comparative analysis of this test with the Kolmogorov test is carried out. It is shown that it is possible to select the correct distribution function and the hypothetical function different from it so that the proposed goodness-of-fit test can have a significantly better performance than the Kolmogorov test. The presented numerical simulation results are in good agreement with the theoretical conclusions.

Key concepts: Goodness of fit, Kolmogorov–Smirnov test, Mathematics, Statistics, Anderson–Darling test, Interval (graph theory), Test (biology), Interval estimation

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