Computing and plotting the distance covariance and correlation function of a univariate or a multivariate time series. Both versions of biased and unbiased estimators of distance covariance and correlation are provided. Test statistics for testing pairwise independence are also implemented. Some data sets are also included. References include: a) Edelmann Dominic, Fokianos Konstantinos and Pitsillou Maria (2019). An Updated Literature Review of Distance Correlation and Its Applications to Time Series. International Statistical Review, 87(2): 237262. <doi:10.1111/insr.12294>. b) Fokianos Konstantinos and Pitsillou Maria (2018). Testing independence for multivariate time series via the autodistance correlation matrix. Biometrika, 105(2): 337352. <doi:10.1093/biomet/asx082>. c) Fokianos Konstantinos and Pitsillou Maria (2017). Consistent testing for pairwise dependence in time series. Technometrics, 59(2): 262270. <doi:10.1080/00401706.2016.1156024>. d) Pitsillou Maria and Fokianos Konstantinos (2016). dCovTS: Distance Covariance/Correlation for Time Series. R Journal, 8(2):324340. <doi:10.32614/RJ2016049>.
Package details 


Author  Michail Tsagris [aut, cre], Maria Pitsillou [aut, cph], Konstantinos Fokianos [aut] 
Maintainer  Michail Tsagris <mtsagris@uoc.gr> 
License  GPL (>= 2) 
Version  1.3 
Package repository  View on CRAN 
Installation 
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