By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting...

Environmental assessment needs of Decision Support Systems (DSSs) able to consider several aspects in a unique analysis framework. The complexity of interaction among ecological, economic and political variables and a widespread lack of data availability lead to difficulty in bringing together...

In the realm of multiscale signal analysis, multifractal analysis provides a natural and rich framework to measure the roughness of a time series. As such, it has drawn special attention of both mathematicians and practitioners, and led them to characterize relevant physiological factors...

Life is one of the most complex nonlinear systems and heart is the core of this lifecycle system. Electrocardiogram (ECG) signals taken from healthy adult subjects have been found to characterize multifractality. In this paper, multiscale analysis method was introduced to find the most effective...

This paper investigates long memory (or long-range dependence) in price returns and volatilities of energy futures contracts with different maturities. Based on a modified rescaled range analysis and three local Whittle methods, the results from rolling sample test suggest that the returns...

By means of wavelet transform, an ARIMA time series can be split into different frequency com- ponents. In doing so, one is able to identify relevant patters within this time series, and there are different ways to utilize this feature to improve existing time series forecasting methods....

Statistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number of wavelet statistics. The analysis can then be rather confusing and even...

Mastering the underlying characteristics of carbon price changes can help governments formulate correct policies to keep efficient operation of carbon markets, and investors take effective measures to evade their investment risks. Empirical mode decomposition (EMD), a self-adaption data analysis...

Statistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number of wavelet statistics. The analysis can then be rather confusing and even...

A variational method for the classical Liouville equation is introduced that facilitates the development of theories for non-equilibrium classical systems. The method is based on the introduction of a complex-valued auxiliary quantity Ψ that is related to the classical position-momentum...