Asymptotic behavior of bootstrapped lower extreme generalized order statistics under linear normalization
Abstract
Abstract This paper investigates the bootstrap behavior of linearly normalized lower extreme m -generalized order statistics ( m -GOSs). We derive sharp conditions for inconsistency, weak consistency, and strong consistency of the bootstrap procedure. Our results refine those of Barakat et al. (“Bootstrap for extreme generalized order statistics,” Arabian J. Sci. Eng. , vol. 36, no. 6, pp. 1083–1090, 2011) by showing that the full-sample bootstrap is inconsistent for all m ≥ 0. In addition, simulation results identify resample sizes that minimize divergence from the target distribution, improving the accuracy of bootstrap approximations.
Fields of Study & Subjects
Statistical Distribution Estimation and Applications
Probability and Statistical Research
Statistical Methods and Inference
Publication details
- Journal / source
- Mathematica Slovaca
- Volume
- 76
- Issue
- 4
- Pages
- 1075–1089
- Publication date
- 28 January 2026
- Language
- EN