A New Lifetime Model, Stochastic Orders and Kidney Infection Regression Model

Document Type : Original Research Articles

Authors
Araf Khanjari Idenak 1
Mohammad Reza Zadkarami 2
Seyed Mohammad Reza Alavi 1
1 Dept. of Statistics, Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Dept. Statistics, Mathematical Sciences and computer college, Shahid Chamran university of Ahvaz, Ahvaz, Iran
10.22059/jsciences.2021.321231.1007639
Abstract
We introduce a method to generate a new class of lifetime models based on the bounded distributions such that the defined models are exclusively a special case of the new class. A new subfamily, Generalized Alpha Power (GAP) is discussed and some stochastic orders in this subfamily are investigated to identify the proposed method effect. The performance of the maximum likelihood estimators based on the simulation is studied and in the end, the importance and flexibility of the new family for the models are illustrated by a real data set. Our results indicate that using the proposed method substantially improves the fitness of any G-family model and can be extended to any real data set. Finally, the GAPTW regression model is applied to the kidney infection data.
Keywords
Bounded Distribution
G-family Model
Lifetime
Regression
Stochastic Orders
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Journal of Sciences, Islamic Republic of Iran
Volume 32, Issue 3
Summer 2021
Pages 245-258