Otsu, Taisuke, Takahata, Keisuke and Xu, Mengshan (2023) Empirical likelihood inference for monotone index model. Japanese Journal of Statistics and Data Science, 6 (1). pp. 103-114. ISSN 2520-8756
![]() |
Text (Otsu_empirical-likelihood-inference--published)
- Published Version
Available under License Creative Commons Attribution. Download (265kB) |
Abstract
This paper proposes an empirical likelihood inference method for monotone index models. We construct the empirical likelihood function based on a modified score function developed by Balabdaoui et al. (Scand J Stat 46:517–544, 2019), where the monotone link function is estimated by isotonic regression. It is shown that the empirical likelihood ratio statistic converges to a weighted chi-squared distribution. We suggest inference procedures based on an adjusted empirical likelihood statistic that is asymptotically pivotal, and a bootstrap calibration with recentering. A simulation study illustrates usefulness of the proposed inference methods.
Item Type: | Article |
---|---|
Official URL: | https://www.springer.com/journal/42081 |
Additional Information: | © 2023 The Authors |
Divisions: | Economics |
Subjects: | H Social Sciences > HA Statistics |
Date Deposited: | 07 Feb 2023 12:03 |
Last Modified: | 12 Aug 2024 06:27 |
URI: | http://eprints.lse.ac.uk/id/eprint/118123 |
Actions (login required)
![]() |
View Item |