wfGn-package: Estimation of the Hurst Parameter for Contaminated Fractional...
In wonsang/wfGn: Estimation of the Hurst Parameter for Contaminated Fractional Gaussian Noises
Description
Details
Author(s)
References
Examples
Description
Estimates the Hurst parameter of a contaminated fractional Gaussian noises by using the modified Whittle estimator.
Details
Package: wfGn
Type: Package
Version: 1.2-1
Date: 2010-10-29
License: GPL (>=2.0)
LazyLoad: yes
Author(s)
Wonsang You and Jan Beran
References
Wonsang You (2010) Modified Whittle's Maximum Likelihood Estimator for Fractional Gaussian Noises Contaminated by Additive Noises, Technical Reports of the Leibniz Institute for Neurobiology, TR10015.
Percival and Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
Jan Beran (1994) Statistics for Long-Memory Processes, Chapman & Hall.
S. Achard and J.-F. Coeurjolly (2009). Discrete variations of the fractional Brownian in the presence of outliers and an additive noise.
Examples
1
2
3
n<-10000;H<-0.2
z<-perturbFGN(n,H,type="WN",SNR=-10,plot=TRUE)
wFGN(z)
wonsang/wfGn documentation built on May 14, 2019, 9:25 p.m.
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Description Details Author(s) References Examples
Description
Estimates the Hurst parameter of a contaminated fractional Gaussian noises by using the modified Whittle estimator.
Details
| Package: | wfGn |
| Type: | Package |
| Version: | 1.2-1 |
| Date: | 2010-10-29 |
| License: | GPL (>=2.0) |
| LazyLoad: | yes |
Author(s)
Wonsang You and Jan Beran
References
Wonsang You (2010) Modified Whittle's Maximum Likelihood Estimator for Fractional Gaussian Noises Contaminated by Additive Noises, Technical Reports of the Leibniz Institute for Neurobiology, TR10015.
Percival and Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
Jan Beran (1994) Statistics for Long-Memory Processes, Chapman & Hall.
S. Achard and J.-F. Coeurjolly (2009). Discrete variations of the fractional Brownian in the presence of outliers and an additive noise.
Examples
1 2 3 | n<-10000;H<-0.2
z<-perturbFGN(n,H,type="WN",SNR=-10,plot=TRUE)
wFGN(z)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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