On Fisher–Bhattacharyya Information Function and Lower Bounds under Right Random Censoring
In this paper, we prove that Fisher information in right random censoring can be decomposed by terms of a failure rate densities. Furthermore, we give an example that variance of unbiased estimate does not achieved Cramer–Rao lower bound, but the second order Bhattacharyya bound is attainable. For a special subfamily of exponential distribution in proportional hazard assumption prove that sequence of Bhattacharyya lower bounds tends to the variance of unbiased polynomial.
Authors
- N. S. Nurmukhamedova (ORCID: https://orcid.org/0000-0002-4672-1722)
- F. A. Abdushukurov (ORCID: https://orcid.org/0000-0002-0185-7159)
- A. A. Abdushukurov (ORCID: https://orcid.org/0000-0002-0994-8127)
Institutions
- Moscow State University (TJ)
- National University of Uzbekistan (UZ)
- Tashkent State University of Economics (UZ)
- Westminster International University in Tashkent (UZ)
Publication Details
- Journal
- Lobachevskii Journal of Mathematics
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1134/s1995080224603011
- Citations
- 2
- Primary Topic
- Statistical Distribution Estimation and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.42