An Improvement of Least Squares Theory: Theory of Least p-Variances Approximation and p-Uncorrelated Functions
Mohammad Masjed-Jamei ()
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Mohammad Masjed-Jamei: Faculty of Mathematics, K. N. Toosi University of Technology, Tehran P.O. Box 16315-1618, Iran
Mathematics, 2025, vol. 13, issue 14, 1-89
Abstract:
We establish a theory whose structure is based on a fixed variable and an algebraic inequality and which improves the well-known least squares theory. The mentioned fixed variable plays a basic role in creating such a theory. In this direction, some new concepts, such as p-covariances with respect to a fixed variable, p-correlation coefficients with respect to a fixed variable, and p-uncorrelatedness with respect to a fixed variable, are defined in order to establish least p-variance approximations. We then obtain a specific system, called the p-covariances linear system, and apply the p-uncorrelatedness condition on its elements to find a general representation for p-uncorrelated variables. Afterwards, we apply the concept of p-uncorrelatedness for continuous functions, particularly for polynomial sequences, and we find some new sequences, such as a generic two-parameter hypergeometric polynomial of the F 3 4 type that satisfies a p-uncorrelatedness property. In the sequel, we obtain an upper bound for 1-covariances, an improvement to the approximate solutions of over-determined systems and an improvement to the Bessel inequality and Parseval identity. Finally, we generalize the concept of least p-variance approximations based on several fixed orthogonal variables.
Keywords: Least p-Variance approximations; least squares theory; p-Covariances and p-Correlation coefficients; p-Uncorrelatedness with respect to a fixed variable; Hypergeometric polynomials; generalized Gram-Schmidt orthogonalization process (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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