International Journal of Statistics and Applied Mathematics
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2023, Vol. 8, Issue 2, Part B

Linearly Immutable Continuously Time Series Modeled Bivariate Stochastic Processes with Vector Values: Distinguishing Features


Author(s): A.I. EL-Deosokey, A. M. Ben Aros, and M. A. Ghazal

Abstract: Certain observations are assumed to be missed while studying finite continual extended Fourier transformations of time series with precisely stable (i+j) vector values. This is assumed to be the case. This is because the procedure requires studying extended finite Fourier transforms in a standardized manner. The goal is to get as close to an exact interpretation of the results as possible with the data at hand. The results will be put to use in decision-making, which is why this is being done. As a result of this new data, the continuously Fourier transformation will take a starring role in the findings. Asymptotic moments are currently receiving a lot of consideration from researchers all over the world. Case studies on the topic of electrical energy will be used to test our theoretical concepts.

DOI: 10.22271/maths.2023.v8.i2b.958

Pages: 94-100 | Views: 43 | Downloads: 6

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How to cite this article:
A.I. EL-Deosokey, A. M. Ben Aros,, M. A. Ghazal. Linearly Immutable Continuously Time Series Modeled Bivariate Stochastic Processes with Vector Values: Distinguishing Features. Int J Stat Appl Math 2023;8(2):94-100. DOI: 10.22271/maths.2023.v8.i2b.958

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