Most Effective Sampling Scheme for Prediction of Stationary Stochastic Processes. (9th July 2022)

• Record Type: Journal Article
• Authors: Saber, Mohammad Mehdi; Shishebor, Zohreh; Raouf, M. M. Abd El; Hafez, E.H.; Aldallal, Ramy
• Other Names: Du Sheng Academic Editor.
• Is Part Of: Complexity. Volume 2022(2022)
• Publication Date: 2022-07-09
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2022/4997675
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : The problem of finding optimal sampling schemes has been resolved in two models. The novelty of this study lies in its cost efficiency, specifically, for the applied problems with expensive sampling process. In discussed models, we show that some observations counteract other ones in prediction mechanism. The autocovariance function of underlying process causes mentioned result. Our interesting result is that, although removing neutralizing observations convert sampling scheme to nonredundant case, it causes to worse prediction. A simulation study confirms this matter, too.