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This is a Quantitative Study study.

October 16, 2025Proceedings of the National Academy of Sciences of Belarus Physics and Mathematics SeriesOpen Access

Orthogonal polynomial multidimensional-matrix regression analysis

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Orthogonal regression analysis using multidimensional matrices showcases improved approximation methods for regression functions.
The article details the derivation of analytical expressions for coefficients involving Fourier series in multidimensional contexts.
Orthogonal polynomials' properties in regression coefficients and measurement error distributions are explored for enhanced statistical modeling.
Computer simulations validate theoretical findings and the efficiency of the proposed mdm orthogonal polynomial regression approach.

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Implication

Observational analysis reveals approximations of functions using orthogonal polynomials in multidimensional matrices, indicating methodological advancements for regression analysis.

Cite This Study

В. С. Муха (2025) studied this question.

synapsesocial.com/papers/68f0f51d8dd8ea469b1d6f9a https://doi.org/10.29235/1561-2430-2025-61-3-203-230

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Implication

Observational analysis reveals approximations of functions using orthogonal polynomials in multidimensional matrices, indicating methodological advancements for regression analysis.

Orthogonal polynomial multidimensional-matrix regression analysis

Key Points

Discussion

Implication

Cite This Study

Orthogonal polynomial multidimensional-matrix regression analysis

Key Points

Discussion

Implication

Cite This Study

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