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A statistical approximation property of the q-Kantorovich-Stancu operators (tilde{S}^{(alpha,beta)}) is obtained in the following theorem.
Secondly, we build a statistical approximation to the output of the computer model, known as a Gaussian process emulator.
In order to tackle this high cost, we build a statistical approximation to the output of the computer model.
In order to address this issue, we build a statistical approximation to the code output and use it to perform sensitivity analysis.
A statistical approximation to the output of a multi-scale constitutive model is adopted to predict the extensibility of wood in the presence of parametric uncertainty.
A simplified approach to this problem is to use a statistical approximation of the simulation ensembles derived from the complex models at a fine scale which will help in reducing the computational burden.
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In [20], they introduced Kantorovich type generalization of q-Szász-Mirakjan operators and discussed their A-statistical approximation properties.
Therefore, this indicates that our A-statistical approximation in Theorem 3.2 is stronger than its classical case.
In this paper, we construct a new family of operators with the help of Erkuş-Srivastava polynomials, establish some A-statistical approximation properties and direct theorems.
In this study, we construct a bivariate generalization of the Szász-Mirakjan-Kantorovich operators based on q-integers and obtain the weighted A-statistical approximation properties of these operators.
In the present paper, a bivariate generalization of the q-Szász-Mirakjan-Kantorovich operators is constructed by q R -integral and these operators' weighted A-statistical approximation properties are established.
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