For stationary time series, the cross-covariance and cross-correlation as functions of lag n serve to quantify similarity two series. The latter measure is also used assess whether cross-correlations are statistically significant. nonstationary analogous measures detrended analysis (DCCA) recently proposed coefficient, ρ(DCCA)(T,n), where T total length series window size. we numerically calculated Cauchy inequality -1 ≤ ρ(DCCA)(T,n) 1. Here derive ρ DCCA)(T,n) 1 for a standard...

There are a number of situations in which several signals simultaneously recorded complex systems, exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can be used to quantify such cross-correlations, as the MF-DCCA based on fluctuation (MF-X-DFA) method. We develop this work class algorithms detrending moving average analysis, called MF-X-DMA. performances MF-X-DMA compared with MF-X-DFA method by extensive numerical...

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these will bias the results. We use partial (DPXA) to uncover intrinsic cross correlations between simultaneously presence of nonstationarity after removing effects other acting as forces. The DPXA method is a generalization that takes into account correlation analysis. demonstrate by bivariate...

Notwithstanding the significant efforts to develop estimators of long-range correlations (LRC) and compare their performance, no clear consensus exists on what is best method under which conditions. In addition, synthetic tests suggest that performance LRC varies when using different generators time series. Here, we performances four [Fluctuation Analysis (FA), Detrended Fluctuation (DFA), Backward Detrending Moving Average (BDMA) Centred (CDMA)]. We use three [Fractional Gaussian Noises two...

Modern technologies not only provide a variety of communication modes, e.g., texting, cellphone conversation, and online instant messaging, but they also detailed electronic traces these communications between individuals. These indicate that the interactions occur in temporal bursts. Here, we study inter-call durations 100,000 most-active users Chinese mobile phone operator. We confirm follow power-law distribution with an exponential cutoff at population level find differences when...

The investigations of financial markets from a complex network perspective have unveiled many phenomenological properties, in which the majority these studies map into one network. In this work, we investigate 30 world stock market indices through their visibility graphs by adopting algorithm to convert each single index graph. A universal allometric scaling law is uncovered minimal spanning trees, whose exponent independent and length index. contrast, maximal trees random do not exhibit...

Housing markets play a crucial role in economies and the collapse of real-estate bubble usually destabilizes financial system causes economic recessions. We investigate systemic risk spatiotemporal dynamics US housing market (1975–2011) at state level based on Random Matrix Theory (RMT). identify richer information largest eigenvalues deviating from RMT predictions for than stock find that component signs eigenvectors contain either geographical or extent differences house price growth rates...

Abstract Much empirical evidence shows that individuals usually exhibit significant homophily in social networks. We demonstrate, however, skill complementarity enhances heterophily the formation of collaboration networks, where people prefer to forge ties with who have professions different from their own. construct a model quantify by assuming choose collaborators maximize utility. Using huge database online societies, we find The results calibration confirm presence heterophily. Both...

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the nature of these cross correlations. However, several important issues about not well understood and most consider only one moment order. We study joint analysis based on partition function with two orders, was initially invented investigate fluid fields, derive analytically properties. apply method numerically binomial measures correlations...

Complex systems are composed of mutually interacting components and the output values these usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method characterizing joint multifractal nature cross correlations, call analysis (MFXWT). We assess performance MFXWT by performing extensive numerical experiments on dual binomial measures with correlations bivariate fractional Brownian motions (bFBMs) monofractal correlations. For measures, find empirical...