Transmuted Generalized Inverse Rayleigh Distribution and Its Applications to Medical Science and Engineering

2018 ◽  
Vol 6 (3) ◽  
pp. 149-163
Author(s):  
Uzma Jan ◽  
Kawsar Fatima ◽  
S. P. Ahmad
Keyword(s):  
Generalized Inverse ◽  
Medical Science ◽  
Rayleigh Distribution ◽  
Science And Engineering

scholarly journals The Medical Science Research and Development Supported by the Korea Science and Engineering Foundation

2005 ◽  
Vol 20 (3) ◽  
pp. 345 ◽  
Author(s):  
Tae-Sun Min ◽  
Jin Han ◽  
Seong-Yong Kim ◽  
Byoung-Doo Rhee ◽  
Myung-Suk Kim
Keyword(s):  
Research And Development ◽  
Medical Science ◽  
Science Research ◽  
Science And Engineering

scholarly journals A New Generalization of the Generalized Inverse Rayleigh Distribution with Applications

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 711
Author(s):  
Rana Ali Bakoban ◽  
Ashwaq Mohammad Al-Shehri
Keyword(s):  
Generalized Inverse ◽  
Real Life ◽  
Likelihood Estimation ◽  
Real Data ◽  
Quantile Function ◽  
Reliability Function ◽  
Rayleigh Distribution ◽  
Information Criteria ◽  
Difference Fields ◽  
The Mean

In this article, a new four-parameter lifetime model called the beta generalized inverse Rayleigh distribution (BGIRD) is defined and studied. Mixture representation of this model is derived. Curve’s behavior of probability density function, reliability function, and hazard function are studied. Next, we derived the quantile function, median, mode, moments, harmonic mean, skewness, and kurtosis. In addition, the order statistics and the mean deviations about the mean and median are found. Other important properties including entropy (Rényi and Shannon), which is a measure of the uncertainty for this distribution, are also investigated. Maximum likelihood estimation is adopted to the model. A simulation study is conducted to estimate the parameters. Four real-life data sets from difference fields were applied on this model. In addition, a comparison between the new model and some competitive models is done via information criteria. Our model shows the best fitting for the real data.

scholarly journals A better approach to discuss medical science and engineering data with a modified Lehmann Type – II model

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 823
Author(s):  
Muhammad Zafar Iqbal ◽  
Muhammad Zeshan Arshad ◽  
Gamze Özel ◽  
Oluwafemi Samson Balogun
Keyword(s):  
Medical Science ◽  
Likelihood Estimation ◽  
Quantile Function ◽  
Model Parameters ◽  
Type Ii ◽  
Reliability Engineering ◽  
Reliability Measures ◽  
Science And Engineering ◽  
Engineering Data ◽  
Engineering Hydrology

Background: Modeling with the complex random phenomena that are frequently observed in reliability engineering, hydrology, ecology, medical science, and agricultural sciences was once thought to be an enigma. Scientists and practitioners agree that an appropriate but simple model is the best choice for this investigation. To address these issues, scientists have previously discussed a variety of bounded and unbounded, simple to complex lifetime models. Methods: We discussed a modified Lehmann type II (ML-II) model as a better approach to modeling bathtub-shaped and asymmetric random phenomena. A number of complementary mathematical and reliability measures were developed and discussed. Furthermore, explicit expressions for the moments, quantile function, and order statistics were developed. Then, we discussed the various shapes of the density and reliability functions over various model parameter choices. The maximum likelihood estimation (MLE) method was used to estimate the unknown model parameters, and a simulation study was carried out to evaluate the MLEs' asymptotic behavior. Results: We demonstrated ML- II's dominance over well-known competitors by modeling anxiety in women and electronic data.

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