| liftLRD-package {liftLRD} | R Documentation |
Wavelet lifting estimators of the Hurst exponent for regularly and irregularly sampled time series
Description
Implementations of Hurst exponent estimators based on the relationship between wavelet lifting scales and wavelet energy
Details
This package exploits a wavelet transform for irregularly spaced data to form wavelet-like scale-based energy measures for a time series. This is then used to estimate the Hurst exponent. The main routine is
liftHurst
Author(s)
Marina Knight, Guy Nason, Matt Nunes
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
References
Knight, M. I, Nason, G. P. and Nunes, M. A. (2017) A wavelet lifting approach to long-memory estimation. Stat. Comput. 27 (6), 1453–1471. DOI 10.1007/s11222-016-9698-2.
For related literature on the lifting methodology adopted in the technique, see
Nunes, M. A., Knight, M. I and Nason, G. P. (2006) Adaptive lifting for nonparametric regression. Stat. Comput. 16 (2), 143–159.
Knight, M. I. and Nason, G. P. (2009) A 'nondecimated' wavelet transform. Stat. Comput. 19 (1), 1–16.
For more information on long-memory processes, see e.g.
Beran, J. et al. (2013) Long-memory processes. Springer.