Unified Hybrid Censoring Samples from Power Pratibha Distribution and Its Applications - Hebatalla H. Mohammad; Khalaf S. Sultan; Mahmoud M. M. Mansour (Mathematics)
This paper suggests an extensive inferential method for the Power Pratibha Distribution (PPD) under Unified Hybrid Censoring Schemes (UHCSs), since there is a growing interest in flexible models in both reliability and service operations. This work studies the PPD model using standard Maximum Likelihood Estimation methods and modern Bayesian approaches too. Using a complex architecture, UHCS simulates tests more closely to what is done in practice than by using more basic censoring schemes. Using analysis, the probability and statistical ranges are carefully calculated for the parameters. Tests demonstrate that Bayesian estimation gives better results than many other methods for estimation, especially when the dataset is not very large and when a lot of data is missing. Real-world tests of electromigration failure data and banking service times help to test the methods. In both situations, the PPD shows it can be used successfully in different reliability settings. By joining advanced censoring models and reliable statistical methods, this research gives a helpful toolset to experts in reliability analysis and statistics.