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For the formation of adequate models of objects of statistical research, with the possible high cost of a measuring experiment or the process of obtaining data, fast and “correct” identification (recognition) of the probability distribution density (PDD) based on the construction of simple histogram estimates is required. The requirement for rapid identification can be considered equivalent to having a limited and small amount of data. The article proposes a theoretically substantiated method for constructing a histogram filter (HF), which is a linear combination of the amount of data in adjacent intervals with constant weight coefficients, which can be expressed in terms of a single coefficient k -the smoothing parameter. The estimation of the smoothing coefficient is based on the minimization of the modified chi-square test. The theorem given in the article establishes that the value of the mathematical expectation of the chisquare test, after applying the HF, decreases by k times compared to the standard mathematical expectation of the criterion with a unit inclusion function.
Ausiannikau Andrei V. 2026. \u201cHistogram Filter with Adjustment of the Smoothing Parameter Based on The Minimization of the Chi-Square Test\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 22 (GJRE Volume 22 Issue J3): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 121
Country: Belarus
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Ausiannikau Andrei V (PhD/Dr. count: 0)
View Count (all-time): 228
Total Views (Real + Logic): 1506
Total Downloads (simulated): 46
Publish Date: 2026 01, Fri
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For the formation of adequate models of objects of statistical research, with the possible high cost of a measuring experiment or the process of obtaining data, fast and “correct” identification (recognition) of the probability distribution density (PDD) based on the construction of simple histogram estimates is required. The requirement for rapid identification can be considered equivalent to having a limited and small amount of data. The article proposes a theoretically substantiated method for constructing a histogram filter (HF), which is a linear combination of the amount of data in adjacent intervals with constant weight coefficients, which can be expressed in terms of a single coefficient k -the smoothing parameter. The estimation of the smoothing coefficient is based on the minimization of the modified chi-square test. The theorem given in the article establishes that the value of the mathematical expectation of the chisquare test, after applying the HF, decreases by k times compared to the standard mathematical expectation of the criterion with a unit inclusion function.
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