Modeling Survival Distributions For Certain Real-World Applications Using Nonparametric Hypothesis Testing

Authors

M. E. Bakr, Department of Statistics and Operation Research, Faculty of Science, King Saud University, P.O. Box2455, Riyadh 11451, Saudi Arabia\\ Department of Basic Sciences, Giza Higher Institute for Engineering, Cairo, EgyptFollow
Arwa M. Alsahangiti, Department of Statistics and Operation Research, Faculty of Science, King Saud University, P.O. Box2455, Riyadh 11451, Saudi ArabiaFollow
A. M. Gadallah, Department of Basic Sciences, Thebes Higher Institute for Engineering, Thebes Academy, Cairo, EgyptFollow

Author Country (or Countries)

Egypt

Abstract

By analyzing the failure behavior of the recorded survival data, we expect to analyze the different processing strategies or functionality of the tools or systems used in this nonparametric statistical test. It is anticipated that the test data would either behave exponentially or like the NBUE Property. If the survival results are NBUE, it is anticipated that the suggested treatment plan would be successful. Contrarily, As shown in the application section, if the data are exponential, the suggested treatment plan wont have any positive or negative consequences on patients. We evaluated the suggested tests efficacy and power for both complete and censored data, compared the outcomes with those of existing tests, and then applied the test to a variety of real-world data to demonstrate its validity.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/jsap/120321

Recommended Citation

E. Bakr, M.; M. Alsahangiti, Arwa; and M. Gadallah, A. (2023) "Modeling Survival Distributions For Certain Real-World Applications Using Nonparametric Hypothesis Testing," Journal of Statistics Applications & Probability: Vol. 12: Iss. 3, Article 21.
DOI: http://dx.doi.org/10.18576/jsap/120321
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol12/iss3/21