The Alpha Power Modified Weibull-Geometric Distribution: A Comprehensive Mathematical Framework with Simulation, Goodness-of-fit Analysis and Informed Decision making using Real Life Data

  • Magrisha Namsaw Department of Statistics, North Eastern Hill University
  • Bhanita Das Department of Statistics, North Eastern Hill University
  • Partha Jyoti Hazarika Department of Statistics, Dibrugarh University
  • Morad Alizadeh Department of Statistics, Faculty of Intelligent systems Engineering and Data Science,Persian Gulf University, Bushehr,75169, Iran
DOI: https://doi.org/10.19139/soic-2310-5070-2607
Keywords: Compounding, Failure Times, Maximum Likelihood Estimation, Lifetime Distribution, Series Structure

Abstract

A new lifetime distribution by compounding the Alpha Power Modified Weibull distribution, named Alpha Power Modified Weibull-Geometric distribution is introduced and discussed.The compounding of the distribution is motivated from the failure time of the system with series structure, where only the minimum lifetime value is considered. Various Statistical properties of the proposed distribution are investigated. Maximum likelihoodestimation method is used to estimate the model parameter. To assess the performance of the proposed method, monte carlo simulation study is conducted using various choices of effective sample size and parameter value. Finally, to illustrate the capability and flexibility of the proposed distribution, three real life data sets are considered and showed that the proposed distribution is more compatible by comparing with other competing lifetime distributions.
Published
2025-07-25
How to Cite
Magrisha Namsaw, Bhanita Das, Partha Jyoti Hazarika, & Alizadeh, M. (2025). The Alpha Power Modified Weibull-Geometric Distribution: A Comprehensive Mathematical Framework with Simulation, Goodness-of-fit Analysis and Informed Decision making using Real Life Data. Statistics, Optimization & Information Computing, 14(2), 1060-1087. https://doi.org/10.19139/soic-2310-5070-2607
Issue
Vol 14 No 2 (2025)
Section
Research Articles
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