Frequency analysis is a technique of fitting a probability distribution to a series of
observations for defining the probabilities of future occurrences of some events of interest …

Time series clustering is an active research area with applications in a wide range of fields.
One key component in cluster analysis is determining a proper dissimilarity measure …

The beginning of the age of artificial intelligence and machine learning has created new
challenges and opportunities for data analysts, statisticians, mathematicians …

The statistical discrimination and clustering literature has studied the problem of identifying
similarities in time series data. Some studies use non-parametric approaches for splitting a …

The traditional approaches to clustering a set of time series are generally applicable if there
is a fixed underlying structure to the time series so that each will belong to one cluster or the …

Purpose This study empirically explores the intraday price discovery mechanism and
volatility transmission effect between the dual-listed Indian Nifty index futures traded …

We present a new way to find clusters in large vectors of time series by using a measure of
similarity between two time series, the generalized cross correlation. This measure …

In some situations, for example in signal processing, economics, electronic, finance, and
climatology, researchers wish to determine whether the two time series are generated by the …

In real world problems, scientists aim to classify and cluster several time series processes
that can be used for a dataset. In this research, for the first time, based on fuzzy clustering …

Full article: Testing the difference between spectral densities of two independent periodically
correlated (cyclostationary) time series models Skip to Main Content Taylor and Francis Online …