Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 12, Number 2 (2018), 2962-2994.
Maximum empirical likelihood estimation and related topics
This article develops a theory of maximum empirical likelihood estimation and empirical likelihood ratio testing with irregular and estimated constraint functions that parallels the theory for parametric models and is tailored for semiparametric models. The key is a uniform local asymptotic normality condition for the local empirical likelihood ratio. This condition is shown to hold under mild assumptions on the constraint function. Applications of our results are discussed to inference problems about quantiles under possibly additional information on the underlying distribution and to residual-based inference about quantiles.
Electron. J. Statist., Volume 12, Number 2 (2018), 2962-2994.
Received: February 2017
First available in Project Euclid: 19 September 2018
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Digital Object Identifier
Peng, Hanxiang; Schick, Anton. Maximum empirical likelihood estimation and related topics. Electron. J. Statist. 12 (2018), no. 2, 2962--2994. doi:10.1214/18-EJS1471. https://projecteuclid.org/euclid.ejs/1537344589