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Maximum Entropy Bootstrap Algorithm Enhancements

Hrishikesh D. Vinod

Fordham University - Department of Economics

June 25, 2013

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.

Number of Pages in PDF File: 15

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

JEL Classification: C22, C23, C15

working papers series

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Date posted: June 26, 2013  

Suggested Citation

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

Contact Information

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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