Maximum Entropy Bootstrap for Time Series: The meboot R Package
The maximum entropy bootstrap is an algorithm that creates an ensemble for time series inference. Stationarity is not required and the ensemble satisfies the ergodic theorem and the central limit theorem. The meboot R package implements such algorithm. This document introduces the procedure and illustrates its scope by means of several guided applications.
References listed on IDEAS
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- Vinod, H. D., 2004. "Ranking mutual funds using unconventional utility theory and stochastic dominance," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 353-377, June.
- Vinod, Hrishikesh D., 2006. "Maximum entropy ensembles for time series inference in economics," Journal of Asian Economics, Elsevier, vol. 17(6), pages 955-978, December.
- Yves Croissant & Giovanni Millo, . "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, American Statistical Association, vol. 27(i02).
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