Rainfall data modeling using improved adaptive type-II progressively censored Weibull-exponential samples
Refah Alotaibi, Mazen Nassar, Ahmed Elshahhat · 2024
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Description
Refah Alotaibi, Mazen Nassar, and Ahmed Elshahhat use rainfall data to test a new way of handling incomplete experiments, in a 2024 statistics paper. Long studies often end with some items untested, a setup called censoring. Their censoring scheme adapts as results arrive, gaining information without waiting for every item.
The authors suppose lifetimes follow a mixed Weibull-exponential model and estimate its parameters two ways. The classic likelihood route gives point and interval estimates. The Bayesian route adds prior beliefs and computes intervals by simulation. Simulated contests compare the two routes under varied plans. Two real rainfall datasets then show the methods at work, with checks to pick the best censoring plan. The work serves engineers and weather analysts who test under time limits.
Catalog record
| CREATOR | Refah Alotaibi, Mazen Nassar, Ahmed Elshahhat |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 355 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |