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Related papers: Analysis of delay correlation matrices

200 papers

Comparing paleoclimate time series is complicated by a variety of typical features, including irregular sampling, age model uncertainty (e.g., errors due to interpolation between radiocarbon sampling points) and time uncertainty…

Applications · Statistics 2019-03-29 Jasper G. Franke , Reik V. Donner

As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming more aware of the relevance of their work to help tackle…

Machine Learning · Statistics 2020-12-23 Federico Amato , Fabian Guignard , Sylvain Robert , Mikhail Kanevski

The dynamics of networks of interacting systems depends intricately on the interaction topology. When the dynamics is explored, generally the whole topology has to be considered. However, we show that there are certain mesoscale subgraphs…

Chaotic Dynamics · Physics 2012-07-06 Anne-Ly Do , Johannes Höfener , Thilo Gross

By an inductive reasoning, and based on recent results of the joint moments of proper delay times of open chaotic systems for ideal coupling to leads, we obtain a general expression for the distribution of the partial delay times for an…

Mesoscale and Nanoscale Physics · Physics 2017-11-28 A. M. Martínez-Argüello , A. A. Fernández-Marín , M. Martínez-Mares

Distributed lag models (DLMs) express the cumulative and delayed dependence between pairs of time-indexed response and explanatory variables. In practical application, users of DLMs examine the estimated influence of a series of lagged…

Applications · Statistics 2018-01-23 Alastair Rushworth

Recent years have witnessed the surge of asynchronous parallel (async-parallel) iterative algorithms due to problems involving very large-scale data and a large number of decision variables. Because of asynchrony, the iterates are computed…

Optimization and Control · Mathematics 2021-02-05 Zhimin Peng , Yangyang Xu , Ming Yan , Wotao Yin

In this paper we employ methods from Statistical Mechanics to model temporal correlations in time series. We put forward a methodology based on the Maximum Entropy principle to generate ensembles of time series constrained to preserve part…

Statistical Mechanics · Physics 2020-07-15 Riccardo Marcaccioli , Giacomo Livan

This is the first of two subsequent publications where the probability distribution of delay-times in scattering of wave packets is discussed. The probability distribution is expressed in terms of the on-shell scattering matrix, the…

Mathematical Physics · Physics 2017-05-24 Uzy Smilansky

We consider wave propagation in a complex structure coupled to a finite number $N$ of scattering channels, such as chaotic cavities or quantum dots with external leads. Temporal aspects of the scattering process are analysed through the…

Mathematical Physics · Physics 2019-12-12 Aurélien Grabsch , Dmitry V. Savin , Christophe Texier

Financial correlations play a central role in financial theory and also in many practical applications. From theoretical point of view, the key interest is in a proper description of the structure and dynamics of correlations. From…

Statistical Mechanics · Physics 2009-11-10 Szilard Pafka , Imre Kondor

The aim of this work is to make a survey on recent sufficient optimality conditions for optimal control problems with time delays in both state and control variables. The results are obtained by transforming delayed optimal control problems…

Optimization and Control · Mathematics 2020-08-10 Ana P. Lemos-Paiao , Cristiana J. Silva , Delfim F. M. Torres

In most realistic models for quantum chaotic systems, the Hamiltonian matrices in unperturbed bases have a sparse structure. We study correlations in eigenfunctions of such systems and derive explicit expressions for some of the correlation…

Quantum Physics · Physics 2017-12-06 Jiaozi Wang , Wen-ge Wang

The Empirical Mode Decomposition (EMD) provides a tool to characterize time series in terms of its implicit components oscillating at different time-scales. We apply this decomposition to intraday time series of the following three…

Computational Engineering, Finance, and Science · Computer Science 2018-04-04 Noemi Nava , T. Di Matteo , Tomaso Aste

We study a network of coupled logistic maps whose interactions occur with a certain distribution of delay times. The local dynamics is chaotic in the absence of coupling and thus the network is a paradigm of a complex system. There are two…

Chaotic Dynamics · Physics 2009-02-03 Marcelo Ponce , C. Masoller , Arturo C. Marti

We derive fidelity decay and parametric energy correlations for random matrix ensembles where time--reversal invariance of the original Hamiltonian is broken by the perturbation. Like in the case of a symmetry conserving perturbation a…

Quantum Physics · Physics 2015-05-27 H. Kohler , T. Nagao , H. -J. Stöckmann

We investigate the spectral distribution of random matrix ensembles with correlated entries. We consider symmetric matrices with real valued entries and stochastically independent diagonals. Along the diagonals the entries may be…

Probability · Mathematics 2015-03-13 Olga Friesen , Matthias Löwe

Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series. This study introduces a new method for predicting the future state of synchronization of the dynamics of two financial time series. To this…

Statistical Finance · Quantitative Finance 2022-11-03 Mostafa Shabani , Martin Magris , George Tzagkarakis , Juho Kanniainen , Alexandros Iosifidis

Complete chaotic synchronization of end lasers has been observed in a line of mutually coupled, time-delayed system of three lasers, with no direct communication between the end lasers. The present paper uses ideas from generalized…

Chaotic Dynamics · Physics 2009-11-11 Alexandra S. Landsman , Ira B. Schwartz

Time-varying volatility is an inherent feature of most economic time-series, which causes standard correlation estimators to be inconsistent. The quadrant correlation estimator is consistent but very inefficient. We propose a novel…

Econometrics · Economics 2023-11-01 Peter Reinhard Hansen , Yiyao Luo

In this paper we develop a novel hidden Markov graphical model to investigate time-varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and…

Methodology · Statistics 2024-12-06 Beatrice Foroni , Luca Merlo , Lea Petrella