Usue Mori, Alexander Mendiburu, J.A. Lozano
This package provides a set of commonly used distance measures for time series data. The application of these distance measures is useful to perform clustering, classification or other data mining tasks.

zoo, xts, dtw, TSclust, KernSmooth, locpol, pdc,
longitudinalData, cluster
A set of commonly used distance measures for time series data. The application of these distance measures is useful to perform clustering, classification or other data mining tasks.

A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.

zoo, xts, dtw, TSclust, KernSmooth, locpol, pdc,
longitudinalData, cluster, methods, graphics, stats

c(person("Usue", "Mori", email = "usue.mori@ehu.eus",role = c("aut", "cre")),person("Alexander", "Mendiburu", role = c("aut")),person("Jose A.", "Lozano", role = c("aut")),person("Duarte", "Folgado", role = c("ctb")))
Usue Mori [aut, cre],
Alexander Mendiburu [aut],
Jose A. Lozano [aut],
Duarte Folgado [ctb]

cluster, dtw, graphics, KernSmooth, locpol, longitudinalData,
methods, pdc, stats, TSclust, xts, zoo
A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series. U. Mori, A. Mendiburu and J.A. Lozano (2016), <doi:10.32614/RJ-2016-058>.

Multiscale Multifractal Analysis of Time Series Data
c(person("Vishakh", "Padmakumar", email = "vishakhpadmakumar@gmail.com", role = c("aut", "cre")), person("Rishab", "Ranga", email = "rishab.ranga1996@gmail.com", role = c("aut")), person("Amogha", "Udupa", email = "amogha15@gmail.com", role = c("aut")), person("Param", "Hanji", email = "param.catchchaos@gmail.com", role = c("aut")))
Multiscale multifractal analysis (MMA) (Gierałtowski et al.,
2012)<DOI:10.1103/PhysRevE.85.021915> is a time series analysis method,
designed to describe scaling properties of fluctuations within the signal
analyzed. The main result of this procedure is the so called Hurst surface
h(q,s) , which is a dependence of the local Hurst exponent h (fluctuation
scaling exponent) on the multifractal parameter q and the scale of observation s
(data window width).
Vishakh Padmakumar [aut, cre],
Rishab Ranga [aut],
Amogha Udupa [aut],
Param Hanji [aut]