Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 11, Number 1 (2017), 2295-2320.
Local optimization-based statistical inference
This paper introduces a local optimization-based approach to test statistical hypotheses and to construct confidence intervals. This approach can be viewed as an extension of bootstrap, and yields asymptotically valid tests and confidence intervals as long as there exist consistent estimators of unknown parameters. We present simple algorithms including a neighborhood bootstrap method to implement the approach. Several examples in which theoretical analysis is not easy are presented to show the effectiveness of the proposed approach.
Electron. J. Statist., Volume 11, Number 1 (2017), 2295-2320.
Received: November 2016
First available in Project Euclid: 27 May 2017
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Xiong, Shifeng. Local optimization-based statistical inference. Electron. J. Statist. 11 (2017), no. 1, 2295--2320. doi:10.1214/17-EJS1292. https://projecteuclid.org/euclid.ejs/1495850626