Average calibration of high-dimensional jackknife empirical likelihood

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Abstract

This paper investigates calibration of the jackknife empirical likelihood for U-statistics and U-shaped estimating equations. By adjusting the mean and variance of the asymptotic distribution, we propose two calibration methods that control the Type I error rate in high-dimensional settings. To overcome their limitations, we develop an average calibration method for the high-dimensional jackknife empirical likelihood. Numerical results show that this average calibration significantly outperforms standard approaches.

Keywords

jackknife empirical likelihood / high-dimensional data / U-statistics / U-shaped estimating equation

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