Testing EBUmg f Class of Life Distributions based on Laplace Transform Technique

2022

Preprint

Self Cite

In biomedical sciences, the application of probability models for survival experience has become increasingly significant. Survival models of classes of life distributions summarize the pattern of survival, recommend additional research, and offer theories and hypotheses. Nowadays, reliability is extremely crucial because complicated scientific gadgets, such as precise medical equipment, airplane equipment, and air defense equipment, are employed for exact scientific reasons. Furthermore, low or no reliability might result in an increase in the cost of device parts (spare parts), the loss of a person, or a threat to national security. For decades, researchers have examined the use of the Laplace transform approach to test exponentiality. We proposed new tests for new better than utilized in expectation class in this post (NBUE). Critical values that have been censored and those that have not been censored are calculated. To evaluate the performance of this test, the powers for numerous regularly used alternatives are determined. The proposed test appears to have high efficacy and good powers for many regularly used alternatives. Finally, sets of medical real data are utilized to demonstrate how the proposed tests can be applied to solve real-world problems.

“…Recently Atallah et al [6] devised a new way to test exponentiality that is more generic and flexible than the goodness approach and Al-Gashgari et al [7] and Gadallah [8] followed them.…”

Section: Definition 12mentioning

confidence: 99%

Solving Fundamental Life Testing Issues: An Application in Medical Science

Bakr

Gadallah

2022

Preprint

Self Cite

“…Several authors, including Gadallah [15] and EL-Sagheer et al [16], examined testing exponentiality using the Laplace transform technique after it was first investigated by Atallah et al [17].…”

Section: Introductionmentioning

confidence: 99%

Non-Parametric Hypothesis Testing for Unknown Aged Class of Life Distribution Using Real Medical Data

Bakr

2023

Axioms

Over the last few decades, the statisticians and reliability analysts have looked at putting exponentiality to the test using the Laplace transform technique. The non-parametric statistical test used in this study, which is based on this technique, evaluates various treatment modalities by looking at failure behavior in the survival data that were gathered. Following use of the suggested strategy, patient survival times are recorded. In this investigation, it was presupposed that the Laplace transform order of (UBAC2) attribute or the constant failure rate would determine how the observed data behave (exponential scenario). If the survival data are exponential, the recommended treatment approach is ineffective. If the survival data are UBAC2L, the technique in use produces a better or a higher expected total present value than an older one governed by an exponential survival function (discussed in the Applications section). The efficiency and critical values of the test are calculated and compared to those of other tests in order to ensure that the suggested statistical test is applied correctly.

“…Al-Gashgari et al [19] and Gadallah [20] followed Atallah et al [21] in developing a new approach of exponential testing that is more generic and flexible than goodness of fit. This is how the research is structured: in Section 2, we produce a test statistic for the complete data using the Laplace transform approach.…”

Section: Introductionmentioning

confidence: 99%

“…Al-Gashgari et al [ 19 ] and Gadallah [ 20 ] followed Atallah et al [ 21 ] in developing a new approach of exponential testing that is more generic and flexible than goodness of fit.…”

Section: Introductionmentioning

confidence: 99%

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

Gadallah

Mohammed

Computational and Mathematical Methods in Medicine

et al. 2022

Self Cite

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.