Rayleigh Current Record Distributed Data: Estimation and Prediction with Application on Saudi Arabia Industrial Data

Ramy Aldallal

Journal of Statistical Theory and Applications2026https://doi.org/10.1007/s44199-025-00150-xarticle
ABDC C
Weight
0.37

What the paper says

Abstract In this paper, we tried to analyze current record data when the primary data already follows the Rayleigh distribution. The current record is a method that works somewhat like the usual record (upper and lower), but in this case, we store them together each time one of them is updated, and do not change the other. By subtracting them in each step, we obtain the record range. We will find some closed forms for the cumulative distribution functions (CDFs) of the upper current record and the lower current record, along with their probability density functions (PDFs). Additionally, some easily calculated formulas for both types will be introduced, along with an estimate for the new proposed distribution’s parameters. A prediction algorithm will be developed to enhance the applicability of the prediction process. Finally, two examples will be used to demonstrate the valuable application of the paper’s findings: one is a simulation study, and the other is a real-life dataset from Saudi Arabia’s industrial sector.

1 citation

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1007/s44199-025-00150-x

Or copy a formatted citation

@article{ramy2026,
  title        = {{Rayleigh Current Record Distributed Data: Estimation and Prediction with Application on Saudi Arabia Industrial Data}},
  author       = {Ramy Aldallal},
  journal      = {Journal of Statistical Theory and Applications},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s44199-025-00150-x},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Rayleigh Current Record Distributed Data: Estimation and Prediction with Application on Saudi Arabia Industrial Data

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.