Bandwidth Selection in Blocks Empirical Likelihood Method for Time Series

In the analysis of time series data with serial correlations, blocks empirical likelihood is an effective nonparametric method to implement statistical inference without specific assumption on the dependence structure. It is noted in many literatures that the bandwidth plays a great role in blocks e...

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Bibliographic Details
Published in:Journal of statistical theory and practice 2022-09, Vol.16 (3), Article 34
Main Authors: Qiu, Jin, Zhu, Weining
Format: Article
Language:English
Subjects:
Mathematics and Statistics
Original Article
Probability Theory and Stochastic Processes
Statistical Theory and Methods
Statistics
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Summary:In the analysis of time series data with serial correlations, blocks empirical likelihood is an effective nonparametric method to implement statistical inference without specific assumption on the dependence structure. It is noted in many literatures that the bandwidth plays a great role in blocks empirical likelihood inference. This paper reviews several methods on the selection of optimal bandwidth in blocks empirical likelihood and block bootstrap for dependent time series data. We also propose a cross validation method for the selection of bandwidth. A comprehensive simulation study is conducted to compare these methods. Based on the results of Monte Carlo simulations, we put forward some practical suggestions on the optimal bandwidth selection.
ISSN:1559-8608
1559-8616
DOI:10.1007/s42519-022-00262-y