
A sequence \(x=(x_k)\) is said to be statistically convergent to \(L\), \(L=st-\lim x\), if and only if for all \(\varepsilon>0\) the set \(K_\varepsilon=\{k\in\mathbb N: |x_k-L|\geq\varepsilon\}\) has natural density zero. If \(p=(p_k)\) is a sequence of nonnegative integers, with \(p_0>0\) and \(P_n=\sum^n_0 p_k\to +\infty\) as \(n\to+\infty\), and if \(t_n=P_n^{-1}\sum_0^n p_k x_k\), \(n=0,1,\dots\), then \(x=(x_k)\) is said to be statistically summable to \(L\) by the weighted mean method determined by the sequence \((p_k)\) if and only if \(st-\lim_n t_n=L\). Using here a weighted density function, the authors define a notion of weighted statistical convergence \((S_{\overline N}\)-convergence), a modification of a concept defined by \textit{V. Karakaya} and \textit{T. A. Chishti} [``Weighted statistical convergence'', Iran. J. Sci. Technol. Trans. A Sci. 33, 219--223 (2009)], and determine the relationship between this concept and the statistical summability method given by \textit{F. Móricz} and \textit{C. Orhan} [Stud. Sci. Math. Hung. 41, No. 4, 391--403 (2004; Zbl 1063.40007)]. Finally, the authors employ this new method so as to establish another approximation theorem of Korovkin type.
density, statistical summability, Korovkin type approximation theorem, Summability methods using statistical convergence, Approximation by positive operators, positive linear operator, statistical convergence, weighted statistical convergence
density, statistical summability, Korovkin type approximation theorem, Summability methods using statistical convergence, Approximation by positive operators, positive linear operator, statistical convergence, weighted statistical convergence
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