Maximum Entropy Bootstrap Algorithm Enhancements

15 Pages Posted: 26 Jun 2013

See all articles by Hrishikesh D. Vinod

Hrishikesh D. Vinod

Fordham University - Department of Economics

Date Written: June 25, 2013

Abstract

While moving block bootstrap (MBB) has been used for mildly dependent (m-dependent) time series, maximum entropy (ME) bootstrap (meboot) is perhaps the only tool for inference involving perfectly dependent, nonstationary time series, possibly subject to jumps, regime changes and gaps. This brief note describes the logic and provides the R code for two potential enhancements to the meboot algorithm in \citet{VinodJavier:2009}, available as the "meboo" package of the R software. The first "rescaling enhancement" adjusts the of meboot resampled elements so that the population variance of the ME density equals that of the original data. Our second "symmetrizing enhancement" forces the ME density to be symmetric. One simulation involving inference for regression standard errors suggests that the symmetrizing enhancement of the meboot continues to outperform the MBB.

Keywords: maximum entropy, block bootstrap, variance, symmetry, R software

JEL Classification: C22, C23, C15

Suggested Citation

Vinod, Hrishikesh D., Maximum Entropy Bootstrap Algorithm Enhancements (June 25, 2013). Available at SSRN: https://ssrn.com/abstract=2285041 or http://dx.doi.org/10.2139/ssrn.2285041

Hrishikesh D. Vinod (Contact Author)

Fordham University - Department of Economics ( email )

Dealy Hall
Bronx, NY 10458
United States
718-817-4065 (Phone)
718-817-3518 (Fax)

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