Forthcoming

Estimation of Confidence Sets for the Parameters of Unit Generalized Rayleigh Model under Records Data

Accepted - December 2022

Authors

Keywords:

Unit generalized Rayleigh distribution, records data, pivotal quantity estimation, confidence sets, non-linear optimization

Abstract

This paper discusses the confidence sets estimation for the unit generalized Rayleigh distribution parameters when the record value is available. By constructing series of pivotal quantities, equal-tailed confidence intervals and region are constructed for unknown parameters. Further, optimal confidence sets with minimum-size are also pursued by using the non-linear optimization technique, whereas various numerical algorithms are also established to obtain the estimates in consequence. For comparison and complementary, traditional likelihood-based asymptotic confidence sets of the parameters are also constructed. Extensive simulation studies are carried out to evaluate the performance of different methods and two real-life examples are used to present their applicability. Additionally, some alternative extension works are also presented for pursuing high-accuracy confidence sets under proposed criteria and the effectiveness of the extended results is also investigated correspondingly.

Additional Files

Published

2022-12-06

How to Cite

Zuo, X., Wang, L., Lio, Y., & Tripathi, Y. M. (2022). Estimation of Confidence Sets for the Parameters of Unit Generalized Rayleigh Model under Records Data: Accepted - December 2022. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/448

Issue

Section

Forthcoming Paper