CNLTtsa-package {CNLTtsa}

Complex-Valued Wavelet Lifting for Univariate and Bivariate Time Series Analysis

Description

Implementations of recent complex-valued wavelet spectral procedures for analysis of irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.

Details

The DESCRIPTION file:

Package:	CNLTtsa
Type:	Package
Title:	Complex-Valued Wavelet Lifting for Univariate and Bivariate Time Series Analysis
Version:	0.1-2
Date:	2018-07-18
Author:	Jean Hamilton [aut], Matt Nunes [aut, cre], Marina Knight [ctb], Piotr Fryzlewicz [ctb]
Authors@R:	c(person("Jean", "Hamilton", role="aut"),person("Matt","Nunes", role=c("aut","cre"),email="[e-mail]"),person("Marina", "Knight", role="ctb"), person("Piotr", "Fryzlewicz", role="ctb"))
Maintainer:	Matt Nunes <[e-mail]>
Description:	Implementations of recent complex-valued wavelet spectral procedures for analysis of irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.
License:	GPL-2
Depends:	R(>= 3.1), adlift, nlt, CNLTreg, fields

Index of help topics:

Baidu                   End of second returns for Google from 1st March
                        2011
CNLTtsa-package         Complex-Valued Wavelet Lifting for Univariate
                        and Bivariate Time Series Analysis
Google                  End of second returns for Google from 1st March
                        2011
cnlt.biv                Performs 'nondecimated' complex-valued wavelet
                        lifting for bivariate time series analysis
cnlt.spec               A function to compute CNLT spectral quantities
                        for univariate and bivariate series
cnlt.univ               Performs 'nondecimated' complex-valued wavelet
                        lifting for univariate time series analysis
cnltspec.plot           A function to plot CNLT spectral quantities of
                        interest
pre.per                 Functions to form periodogram objects with a
                        common time and scale bins for bivariate series
                        with different sampling grids for each
                        component
smooth.over.scale       Function to perform smoothing over scale of
                        spectral quantities
smooth.over.time        Function to perform smoothing over time of
                        spectral quantities

The main routines of the package are cnlt.univ and cnlt.biv which perform the nondecimated complex-valued lifting transform for univariate and bivariate time series, respectively; cnlt.spec computes spectral quantities of interest, for example the coherence and phase between two components of a bivariate series.

Author(s)

Jean Hamilton [aut], Matt Nunes [aut, cre], Marina Knight [ctb], Piotr Fryzlewicz [ctb]

Maintainer: Matt Nunes <[e-mail]>

References

Hamilton, J., Nunes, M. A, Knight, M. I. and Fryzlewicz, P. (2018) Complex-valued wavelet lifting and applications. Technometrics, 60 (1), 48-60, DOI 10.1080/00401706.2017.1281846.

For related literature on the lifting methodology adopted in the technique, see

Knight, M. I. and Nason, G. P. (2009) A 'nondecimated' wavelet transform. Stat. Comput. 19 (1), 1–16.

Knight, M. I., Nunes, M. A. and Nason, G. P. (2012) Spectral Estimation for Locally Stationary Time Series with Missing Observations. Stat. Comput. 22 (4), 877–895.

See Also

cnlt.reg