THE OPTIMAL STEIN ESTIMATION RELATIVE TO CONCENTRATION PROBABILITY – A LARGE SAMPLE APPROXIMATION

Authors

  • Raman Pant Dept. of Statistics, Mahatma Gandhi Kashi Vidyapith Varanasi

Keywords:

Linear regression model, Stein rule estimator, large sample approximation, Sampling distribution, concentration probability

Abstract

General family of Stein rule estimators is considered in linear regression model. The large sample approximation of its sampling distribution is derived. Approximations of concentration probability of the estimators around the true value are evaluated. Optimal selection of the biasing scalar is discussed.

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Published

2023-04-12

How to Cite

Pant, R. (2023). THE OPTIMAL STEIN ESTIMATION RELATIVE TO CONCENTRATION PROBABILITY – A LARGE SAMPLE APPROXIMATION. Investigación Operacional, 39(4). Retrieved from https://revistas.uh.cu/invoperacional/article/view/3850

Issue

Vol. 39 No. 4 (2018): Investigación Operacional

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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