Bayes Estimation of a Common Mean of Several Normal Populations with Unknown Variances
Combining information from several independent normal populations to estimate a common mean parameter has applications in meta-analysis and is an important statistical problem. For this application, Gregurich and Broemeling (1997) and Tu (2012) concentrated on point estimation employing Bayesian techniques to infer about the common mean of two normal populations with unknown variances. In our study, we expand upon their investigation to encompass k normal populations with a common mean, incorporating a range of objective priors. Through the use of two examples, it is discovered that as the hyperparameter α under a Bayesian framework increases, the performance of the Bayesian technique also improves. IJSS, Vol. 24(2) Special, December, 2024, pp 81-94
Authors
- Yehenew G. Kifle (ORCID: https://orcid.org/0000-0002-5583-6601)
- Chioneso Show Marange (ORCID: https://orcid.org/0000-0002-8960-7268)
- Peter M. Mphekgwana (ORCID: https://orcid.org/0000-0002-3068-9406)
Institutions
- University of Fort Hare (ZA)
- University of Maryland, Baltimore County (US)
- University of Limpopo (ZA)
Publication Details
- Journal
- International Journal of Statistical Sciences
- Published
- 2024-12-23
- DOI
- https://doi.org/10.3329/ijss.v24i20.78216
- Primary Topic
- Bayesian Methods and Mixture Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00