SHRINKAGE ESTIMATION OF THE TTT OF THE LOMAX DISTRIBUTION UNDER PROGRESSIVE TYPE II CENSORING

Shrinkage estimation is a robust procedure that integrates an unbiased estimate with the current estimate using a weighted factor. Several weighted factors dynamically adjust the shrinkage factor based on the sample size and censoring proportion, ensuring that the method tailors the shrinkage to the available data rather than applying a constant factor. Despite certain real-world application limitations, the Lomax distribution exhibits flexibility as a tail-behaviour modelling technique, making it particularly suitable for reliability and survival analysis. The present study focuses on estimating the shape parameter of the Lomax distribution using PTII censored sampling within the framework of the shrinkage estimator method. Shrinkage estimators are derived based on constant and shrinkage weight factors under different weight functions. These depend on the base estimate’s sample size, bias, and variance to shrink the current estimate. The performance of these estimators is rigorously evaluated through a Monte Carlo simulation study.