Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package

被引:5
|
作者
Taylor, Simon A. C. [1 ]
Park, Timothy [1 ]
Eckley, Idris A. [1 ]
机构
[1] Univ Lancaster, Dept Math & Stat, Lancaster, England
来源
JOURNAL OF STATISTICAL SOFTWARE | 2019年 / 90卷 / 11期
关键词
mvLSW; multivariate evolutionary wavelet spectrum; coherence; R; TIME-SERIES; MODELS;
D O I
10.18637/jss.v090.i11
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper describes the R package mvLSW. The package contains a suite of tools for the analysis of multivariate locally stationary wavelet (LSW) time series. Key elements include: (i) the simulation of multivariate LSW time series for a given multivariate evolutionary wavelet spectrum (EWS); (ii) estimation of the time-dependent multivariate EWS for a given time series; (iii) estimation of the time-dependent coherence and partial coherence between time series channels; and, (iv) estimation of approximate confidence intervals for multivariate EWS estimates. A demonstration of the package is presented via both a simulated example and a case study with EuStock Markets from the datasets package.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Dynamic classification using multivariate locally stationary wavelet processes
    Park, Timothy
    Eckley, Idris A.
    Ombao, Hernando C.
    [J]. SIGNAL PROCESSING, 2018, 152 : 118 - 129
  • [2] Multivariate locally stationary 2D wavelet processes with application to colour texture analysis
    Sarah L. Taylor
    Idris A. Eckley
    Matthew A. Nunes
    [J]. Statistics and Computing, 2017, 27 : 1129 - 1143
  • [3] Multivariate locally stationary 2D wavelet processes with application to colour texture analysis
    Taylor, Sarah L.
    Eckley, Idris A.
    Nunes, Matthew A.
    [J]. STATISTICS AND COMPUTING, 2017, 27 (04) : 1129 - 1143
  • [4] FactoMineR: An R package for multivariate analysis
    Le, Sebastien
    Josse, Julie
    Husson, Francois
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2008, 25 (01): : 1 - 18
  • [5] Locally Stationary Wavelet Analysis of Nonstationary Turbulent Fluxes
    Arias-Arana, D.
    Fochesatto, G. J.
    Jimenez, R.
    Ojeda, C.
    [J]. BOUNDARY-LAYER METEOROLOGY, 2024, 190 (07)
  • [6] An R package for the forward analysis of multivariate data
    Corbellini, Aldo
    Konis, Kjell
    [J]. DATA ANALYSIS, CLASSIFICATION AND THE FORWARD SEARCH, 2006, : 189 - 197
  • [7] mmeta: An R Package for Multivariate Meta-Analysis
    Luo, Sheng
    Su, Xiao
    Chen, Yong
    chu, Haitao
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2014, 56 (11): : 1 - 26
  • [8] MGLM: An R Package for Multivariate Categorical Data Analysis
    Kim, Juhyun
    Zhang, Yiwen
    Day, Joshua
    Zhou, Hua
    [J]. R JOURNAL, 2018, 10 (01): : 73 - 90
  • [9] adegenet:: a R package for the multivariate analysis of genetic markers
    Jombart, Thibaut
    [J]. BIOINFORMATICS, 2008, 24 (11) : 1403 - 1405
  • [10] Trend locally stationary wavelet processes
    McGonigle, Euan T.
    Killick, Rebecca
    Nunes, Matthew A.
    [J]. JOURNAL OF TIME SERIES ANALYSIS, 2022, 43 (06) : 895 - 917