Statistical Analysis and Data Mining The ASA Data Science Journal, Journal Year: 2024, Volume and Issue: 17(6)
Published: Dec. 1, 2024
ABSTRACT This research aims to study the estimation of parameters for a Burr‐XII distribution and investigate optimal sampling plans under progressive Type‐I censoring (PTIC). For point estimation, we employed maximum‐likelihood (MLE) method using two numerical approaches: Newton–Raphson Expectation–Maximization algorithm. We also utilized Bayesian with squared error loss linear exponential functions. Specifically, approximate methods, Lindley Tierney‐Kadane methods were examined. Additionally, was performed Markov Chain Monte Carlo Metropolis‐Hastings (MH) interval constructed asymptotic confidence intervals MLE highest posterior density within framework. The practical involved simulations assess efficiency accuracy proposed across different PTIC schemes. A real data analysis is provided illustrate application these methodologies in analyzing clinical trial dataset. Data from scheme reveals patterns pain relief, aiding evaluating antibiotic ointment's effectiveness. further investigates PTIC.
Language: Английский
