Modeling Various Survival Distributions using a Nonparametric Hypothesis Testing Based on Laplace Transform Approach with Some Real Applications

Author:

Gadallah A. M.1,Mohammed B. I.2,Al-Babtain Abdulhakim A.3ORCID,Khosa Saima Khan4,Kilai Mutua5ORCID,Yusuf M.6ORCID,Bakr M. E.7ORCID

Affiliation:

1. Department of Basic Sciences, Thebes Higher Institute for Engineering, Thebes Academy, Cairo, Egypt

2. Department of Mathematic. Faculty of Science, Al-Azhar University, First El Mokhaim El Madem St., Nasr City 11884, Cairo 11451, Egypt

3. Department of Statistics and Operation Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

4. Department of Mathematics and Statistics University of Saskatchewan, Saskatoon, SK, Canada

5. Department of Mathematics, Pan African Insitute of Basic Science, Technology and Innovation, Nairobi, Kenya

6. Department of Mathematics, Helwan University, Cairo, Egypt

7. Department of Basic Sciences, Giza Higher Institute for Engineering and Technology, Cairo, Egypt

Abstract

We hope to assess the different processing methodologies or the effectiveness of the devices or systems applied in this nonparametric statistical test by observing the failure behavior of the recorded survival data. The proposed second-order approach of new better than used (NBU 2) will be employed, which requires that the test data behaves either like NBU 2 property or exponentially. If the survival data is NBU 2, the proposed treatment method is likely to be beneficial. If the data are exponential, on the other hand, the recommended treatment method has no positive or negative influence on patients, as shown in the application section. To establish the validity of the test, we calculated the power of the proposed test and efficiency on both complete and censored data, compared the results to those of existing tests, and then applied the test to a range of real-world data.

Funder

King Saud University

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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