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Novel convergence concepts enhance approximation techniques, providing significant theoretical insights.
In the present work, a novel type of convergence is introduced by incorporating the notions of I-statistical convergence and equi-statistical convergence. These offer a more extensive framework in comparison to the classical concepts of I-convergence and statistical convergence. Within this generalized setting, two fundamental approximation results are established and proven: one in the sense of Korovkin-type theorems and another in the sense of a Voronovskaya-type result. Moreover, the paper provides a concrete example that illustrates the practical significance of the new convergence concept. Finally, an estimate for the rate at which I-equi-statistical convergence occurs is provided, thus quantifying the efficiency of approximation under this framework.
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Dirik et al. (2026) studied this question.
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