Improved Robust Estimation Techniques for the Scale Parameter of BirnbaumSaunders Distribution

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ID: 316147
2024
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Abstract
This study investigates the performance of improved estimation of robust estimators for the scale parameter of Birnbaum-Saunders distribution integrating sample information and unknown previous knowledge (non-sample information) by fixing the shape parameter. The three classes of point estimation techniques, linear shrinkage robust estimator, preliminary test robust estimator, and shrinkage preliminary test robust estimator are suggested for more efficient estimation. It is also recommended to use a Wald's test statistic to examine the non-sample data. The asymptotic theoretical properties of the recommended estimators are examined through simulation studies. The performance of the estimators is being evaluated based on simulated relative efficiency. Our simulation results decisively support asymptotic theory. A real data application is also carried out to demonstrate how effectively the suggested estimating methods work in practice
Reference Key
imported_1780933788_6a26e49cb3419 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Waqas Makhdoom, Muhammad Haris Javaid
Journal Journal of Statistics
Year 2024
DOI
DOI not found
URL
https://jstat.gcu.edu.pk/index.php/jstat/article/view/2
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