378 results on '"Donner, Reik"'
Search Results
352. Crustal Deformation Models and Time-Frequency Analysis of GPS Data from Deception Island Volcano (South Shetland Islands, Antarctica)
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Ramírez, María Eva, Berrocoso, Manuel, González, María José, Fernández, Alberto, Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
- Published
- 2008
- Full Text
- View/download PDF
353. Fourier, Scattering, and Wavelet Transforms: Applications to Internal Gravity Waves with Comparisons to Linear Tidal Data
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Hawkins, James A., Warn-Varnas, Alex, Christov, Ivan, Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
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- 2008
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354. Towards Robust Nonlinear Multivariate Analysis by Neural Network Methods
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Hsieh, William W., Cannon, Alex J., Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
- Published
- 2008
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355. Automatic Parameter Estimation in a Mesoscale Model Without Ensembles
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Duane, Gregory S., Hacker, Joshua P., Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
- Published
- 2008
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356. Prediction of Extreme Events
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Hallerberg, Sarah, Bröcker, Jochen, Kantz, Holger, Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
- Published
- 2008
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357. Subsampling Methodology for the Analysis of Nonlinear Atmospheric Time Series
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Gluhovsky, Alexander, Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
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- 2008
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358. Global Patterns of Nonlinearity in Real and GCM-Simulated Atmospheric Data
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Mikšovský, Jiří, Pišoft, Petr, Raidl, Aleš, Bhattacharji, S., editor, Neugebauer, H. J., editor, Reitner, J., editor, Stüwe, K., editor, Friedman, G. M., editor, Seilacher, A., editor, Donner, Reik V., editor, and Barbosa, Susana M., editor
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- 2008
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359. Time-frequency analysis of regularly and irregularly sampled time series : projection and multitaper methods
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Lenoir, Guillaume, UCL - SST/ELI/ELIC - Earth & Climate, UCL - Faculté des Sciences, Crucifix, Michel, De Keersmaecker, Marie-Laurence, Jacques, Laurent, Antoine, Jean-Pierre, Donner, Reik, and Nicolay, Samuel
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Peridogram ,Lomb-Scargle ,Irregularly sampled times series ,Unevenly sampled time series ,ARMA process ,Multitaper method ,Nonstationary processes ,Significance testing ,Scalogram ,Continuous wavelet transform - Abstract
The first part addresses time series which are sampled irregularly along the time axis, as is often seen in geophysical and climatological time series. We provide a general framework for the frequency and time-frequency analysis under irregular sampling, extending and unifying existing methods within the formalism of orthogonal projections. The Lomb-Scargle periodogram is extended to the time-frequency domain through the scalogram of the continuous wavelet transform, which is well-suited for irregularly sampled time series, since it does not require the data to be interpolated in time. The theory is developed for the specific case of the Morlet wavelet, widely used in geophysics. We also propose a test to estimate the significance of deterministic periodic components against an additive stationary Gaussian continuous autoregressive-moving-average process. The second part of the thesis tackles the problem of the estimation of the wavelet power spectrum (WPS) of a continuous-time or regularly sampled nonstationary process from one of its samples. To this end, we transfer the multitaper method (MTM) of Thomson to the wavelet case. The MTM estimator efficiently reduces the variance while minimizing the leakage outside a predefined area in the time-scale plane. The tapers of the MTM are the eigenfunctions of a localization operator in the Hilbert space. The analytical expression of the tapers is only known in specific cases, and an analytical derivation is probably not generalizable to any mother wavelet. This is why we provide a numerical scheme for the estimation of the tapers of any well-localized progressive wavelet. It is also proved that a numerical approach is tractable thanks to some invariance properties. (SC - Sciences) -- UCL, 2017
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- 2017
360. Wie wirken Unternehmensberichte auf den Aktienkurs? - Eine statistische Untersuchung mittels Event Coincidence Analysis und Superposed Epoch Analysis
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Rimatzki, Florian, Donner, Reik, Okhrin, Ostap, Hirte, Georg, and Technische Universität Dresden
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Geschäftsbericht, Aktienkurs, Rendite, Automobilindustrie, Faktorenanalyse, Zeitreihenanalyse ,ddc:330 ,Business Reports, Event Coincidence Analysis, Superposed Epoch Analysis, Stock Prices, Factor Analysis, Time Series ,ddc:510 - Abstract
Several times a year companies publish business reports to openly account for their business activities. This thesis examines the effect of those business reports on stock prices of businesses in the German automotive industry. Different statistical methods such as Event Coincidence Analysis and Superposed Epoch Analysis are used to examine possible negative and positive reactions of stock prices before and after the disclosure of business reports. It shows that there seems to be a stronger influence of a negative business report on the daily abnormal rate of return than of a positive business report. Furthermore the thesis confirms the hypothesis of Roeder that the information from a business report is processed not only on the day of publication but also on the day after.
- Published
- 2016
361. Spatial Constraints and Topology in Urban Road Networks
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Otto, Michael, Donner, Reik, Okhrin, Ostap, and Technische Universität Dresden
- Subjects
ddc:380 ,Komplexe Netzwerke, Straßennetzwerke ,Complex Networks, Road Networks - Abstract
Spatial and topological features of urban road networks have been observed variously in the past. No previous study, however, has investigated and compared an extensive data set from cities all over the world regarding their network properties. In this work, re-spectively 20 large cities from 5 continents and Germany are analyzed. In the process, node degree, link length, shortest paths, detour index as well as measures for rectangu-larity are used to characterize and to differentiate the networks. While most networks properties are quite diverse from continent to continent, the detour index as a measure of efficiency shows remarkable similarities and homogeneity over all regions, independ-ent of their spatial network structure. It is shown that in some cities this efficiency is mainly sustained by a subnetwork of major roads, while in others it relies on a balance between minor and major roads. Rectangularity in all regions is shown to be predomi-nant in the structure of minor road subnetworks, while it is shown that this feature is not trivially connected to the node degree.:Table of Contents List of Figures V List of Tables VI Chapter 1 Introduction 1 Chapter 2 Preliminaries 4 2.1 Complex Networks 4 2.2 Network Characteristics 5 2.2.1 Node Degree 5 2.2.2 Link Length 6 2.2.3 Shortest Path Length 7 2.2.4 Detour Index 7 2.2.5 Rectangularity 8 2.3 Data 11 2.3.1 Data Source and Analyzed Cities 11 2.3.2 Data Structure 12 2.3.3 Data Quality 14 2.4 Data Preprocessing 15 2.4.1 Removal of Dead Ends 16 2.4.2 Removal of Transient Nodes 17 2.4.3 Merging of Multi-Node Intersections and Roads with Separated Lanes 17 2.5 Network Modifications 20 Chapter 3 Results and Discussion 23 3.1 Unmodified Networks 23 3.1.1 Node Degree 23 3.1.2 Link Length 25 3.1.3 Network Efficiency 28 3.1.4 Rectangularity 30 3.2 Modified Networks and Comparison to Unmodified Networks 36 3.2.1 Node Degree 37 3.2.2 Link Length 39 3.2.3 Network Efficiency 41 3.2.4 Rectangularity 46 Chapter 4 Conclusion and Outlook 49 References 51 Appendix A Detailed Results of Unmodified Networks 55 Appendix A.1 Europe 55 Appendix A.2 Anglo America 56 Appendix A.3 Latin America 57 Appendix A.4 Asia 58 Appendix A.5 Africa 59 Appendix A.6 Germany 60 Appendix B Corrupted Networks due to Merging of Intersections with Radius 50 m 61 Appendix C Modification 2 62 Appendix D Spatial Distributions of Network Measures 63 Appendix D.1 Node Degree 63 Appendix D.2 Link Length 64 Appendix D.3 Detour Index 65 Appendix D.4 Rectangularity 66 Appendix E Detailed results of modified networks 67 Appendix E.1 Europe 67 Appendix E.2 Anglo America 68 Appendix E.3 Latin America 69 Appendix E.4 Asia 70 Appendix E.5 Africa 71 Appendix E.6 Germany 72 Räumliche und topografische Eigenschaften urbaner Straßennetzwerke sind in der Ver-gangenheit vielfältig untersucht wurden. Keine der bisherigen Studien hat jedoch eine umfassende Anzahl weltweiter Städte auf ihre Netzwerkeigenschaften untersucht. In dieser Arbeit werden jeweils 20 Großstädte aus 5 Kontinenten analysiert. Knotengrad, Kantenlängen, kürzeste Pfade, Detour Index sowie die Rechtwinkligkeit werden schritt-weise untersucht, um die Netzwerke zu charakterisieren und voneinander zu differen-zieren. Während die meisten Netzwerkmaße große Unterscheide von Kontinent zu Kon-tinent aufweisen, lassen sich beim Detour Index, welcher ein Maß für die Effizienz im Netzwerk dient, bemerkenswerte Gemeinsamkeiten in allen Regionen unabhängig von der räumlichen Netzwerkstruktur feststellen. Es wird gezeigt, dass die Effizienz in eini-gen Städten hauptsächlich durch ein Teilnetz von Hauptstraßen getragen wird, während sie anderswo auf einer Balance zwischen Haupt- und Nebenstraßen beruht. Vor allem in der Struktur von Nebenstraßennetzwerken kann Rechtwinkligkeit festgestellt werden, während gleichzeitig wird, dass letztere in keinem trivialen Zusammenhang mit dem Knotengrad steht.:Table of Contents List of Figures V List of Tables VI Chapter 1 Introduction 1 Chapter 2 Preliminaries 4 2.1 Complex Networks 4 2.2 Network Characteristics 5 2.2.1 Node Degree 5 2.2.2 Link Length 6 2.2.3 Shortest Path Length 7 2.2.4 Detour Index 7 2.2.5 Rectangularity 8 2.3 Data 11 2.3.1 Data Source and Analyzed Cities 11 2.3.2 Data Structure 12 2.3.3 Data Quality 14 2.4 Data Preprocessing 15 2.4.1 Removal of Dead Ends 16 2.4.2 Removal of Transient Nodes 17 2.4.3 Merging of Multi-Node Intersections and Roads with Separated Lanes 17 2.5 Network Modifications 20 Chapter 3 Results and Discussion 23 3.1 Unmodified Networks 23 3.1.1 Node Degree 23 3.1.2 Link Length 25 3.1.3 Network Efficiency 28 3.1.4 Rectangularity 30 3.2 Modified Networks and Comparison to Unmodified Networks 36 3.2.1 Node Degree 37 3.2.2 Link Length 39 3.2.3 Network Efficiency 41 3.2.4 Rectangularity 46 Chapter 4 Conclusion and Outlook 49 References 51 Appendix A Detailed Results of Unmodified Networks 55 Appendix A.1 Europe 55 Appendix A.2 Anglo America 56 Appendix A.3 Latin America 57 Appendix A.4 Asia 58 Appendix A.5 Africa 59 Appendix A.6 Germany 60 Appendix B Corrupted Networks due to Merging of Intersections with Radius 50 m 61 Appendix C Modification 2 62 Appendix D Spatial Distributions of Network Measures 63 Appendix D.1 Node Degree 63 Appendix D.2 Link Length 64 Appendix D.3 Detour Index 65 Appendix D.4 Rectangularity 66 Appendix E Detailed results of modified networks 67 Appendix E.1 Europe 67 Appendix E.2 Anglo America 68 Appendix E.3 Latin America 69 Appendix E.4 Asia 70 Appendix E.5 Africa 71 Appendix E.6 Germany 72
- Published
- 2016
362. Vorhersagbarkeit ökonomischer Zeitreihen auf verschiedenen zeitlichen Skalen
- Author
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Mettke, Philipp, Donner, Reik, Okhrin, Ostap, and Technische Universität Dresden
- Subjects
Discrete Wavelet Transformation (DWT), Singular Spectrum Analysis (SSA), Empirical Mode Decomposition (EMD), Entropy, Predictability, Recurrence Quantification Analysis (RQA), Frequency Analysis, Time Series Analysis ,ddc:330 ,Vorhersagbarkeitsmaße, Diskrete Wavelet-Transformation (DWT), Singulärsystemanalyse (SSA), Empirische Modenzerlegung (EMD), Entropie, Rekurrenzanalyse (RQA), Frequenzanalyse - Abstract
This thesis examines three decomposition techniques and their usability for economic and financial time series. The stock index DAX30 and the exchange rate from British pound to US dollar are used as representative economic time series. Additionally, autoregressive and conditional heteroscedastic simulations are analysed as benchmark processes to the real data. Discrete wavelet transform (DWT) uses wavelike functions to adapt the behaviour of time series on different time scales. The second method is the singular spectral analysis (SSA), which is applied to extract influential reconstructed modes. As a third algorithm, empirical mode decomposition (END) leads to intrinsic mode functions, who reflect the short and long term fluctuations of the time series. Some problems arise in the decomposition process, such as bleeding at the DWT method or mode mixing of multiple EMD mode functions. Conclusions to evaluate the predictability of the time series are drawn based on entropy - and recurrence - analysis. The cyclic behaviour of the decompositions is examined via the coefficient of variation, based on the instantaneous frequency. The results show rising predictability, especially on higher decomposition levels. The instantaneous frequency measure leads to low values for regular oscillatory cycles, irregular behaviour results in a high variation coefficient. The singular spectral analysis show frequency - stable cycles in the reconstructed modes, but represents the influences of the original time series worse than the other two methods, which show on the contrary very little frequency - stability in the extracted details.:1. Einleitung 2. Datengrundlage 2.1. Auswahl und Besonderheiten ökonomischer Zeitreihen 2.2. Simulationsstudie mittels AR-Prozessen 2.3. Simulationsstudie mittels GARCH-Prozessen 3. Zerlegung mittels modernen Techniken der Zeitreihenanalyse 3.1. Diskrete Wavelet Transformation 3.2. Singulärsystemanalyse 3.3. Empirische Modenzerlegung 4. Bewertung der Vorhersagbarkeit 4.1. Entropien als Maß der Kurzzeit-Vorhersagbarkeit 4.2. Rekurrenzanalyse 4.3. Frequenzstabilität der Zerlegung 5. Durchführung und Interpretation der Ergebnisse 5.1. Visuelle Interpretation der Zerlegungen 5.2. Beurteilung mittels Charakteristika 6. Fazit
- Published
- 2015
363. Aktienkurse und Unternehmenszahlen – Eine ökonometrische Analyse des Wechselspiels am Beispiel der Automobilindustrie
- Author
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Koltermann, Philipp, Donner, Reik, Okhrin, Ostap, and Technische Universität Dresden
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ddc:330 ,Shares ,Aktien, Aktienkurse, Unternehmenszahlen - Abstract
Public traded companies are obliged to account for their operating numbers from time to time. These numbers are usually published in their interim and annual reports. Besides annual accounts and their balance sheet, the income statement provides great value for potential investors and shareholders. This master thesis wants to prove that announcements of operating numbers have verifiable influence on share prices. Event studies are mainly used to determine abnormalities in return series. An event study focuses on the prediction of normal returns with the help of a certain market model and ascertains abnormal returns in a second step. The selection of a suitable market model is the essence of every event study. On the one hand, there are market models which use certain external factors in their regression equation, having influence on returns. On the other hand, a widely range of autoregressive models computes returns on the basis of their own precursors. Furthermore an extension to that is even able to detect and map volatility clustering in return series. Eventually the variety of different market models exhibits that return prediction can only be an approach to real observations. Besides the study of abnormalities on a certain event day, it could be worthwhile to examine intervals in return series prior and afterwards an incident. Keynote of this analysis is that investors and shareholders could detect earnings surprises premature and also trade afterwards a publication on an extraordinary basis. The statistical question raised is whether there are coincidences between significantly more distinct trends in return series and the release of business reports. Furthermore, it is arguable whether these coincidences appear only on a random basis or not. In addition to that, time series of capital market values succumb specific statistical characteristics. Properties like a leptokurtic distribution and weak stationarity constitute prerequisites to subsequent analysis. Additionally autocorrelation of returns is taken into particularly consideration. To sum up, it seems that capital markets provide a diversity of attributes to analyse. Taken all together, these procedures try to disprove capital market efficiency.:1 Einleitung 1 2 Theoretische Grundlagen 3 2.1 Bilanzanalyse 3 2.1.1 Rechte und Pflichten 3 2.1.2 Kennzahlen 4 2.2 Analyse des Kapitalmarktes 5 2.2.1 Aktienanalyse und Markteffizienzhypothese 5 2.2.2 Eregnisstudie 7 2.3 Annahmen 9 2.3.1 Datengrundlage 9 2.3.2 Thesenbildung 11 3 Grundlagen zur statistischen Auswertung 12 3.1 Renditeberechnung und –bereinigung 12 3.1.1 Stetige und diskrete Rendite 12 3.1.2 Marktbereinigte Renditen 13 3.1.3 Zeitpunktspezifischer t–Test 16 3.2 Definitionen 16 3.2.1 Stationarität, Leptokurtosis und Normalverteilung 17 3.2.2 Autokorrelation und Autokovarianz 18 3.2.3 White Noise, Random Walk und Lag–Operator 19 3.3 Linear stochastische Prozesse 20 3.3.1 Autoregressive Prozesse 21 3.3.2 Moving–Average–Prozesse 22 3.3.3 Autoregressive–Moving–Average–Prozesse 24 3.4 Modelle zum Volatilitätsclustering 25 3.4.1 ARCH–Modelle 25 3.4.2 GARCH–Modelle 27 3.4.3 Weiterführende Modelle 28 3.5 Berechnung erwarteter Gewinn 29 3.5.1 Hauptkomponentenanalyse 30 3.5.2 Saisonale Regression 31 3.5.3 Gewinnerwartung 33 3.6 Verfahren zu These 2 und 3 33 3.6.1 Koinzidenzanalyse 33 3.6.2 Bootstrapping 35 3.6.3 Monte–Carlo–Simulation 36 4 Literaturübersicht 37 4.1 Bisherige Studien über Gewinneinfluss 37 4.2 Studien mit Bezug auf ARCH–Modelle 38 4.3 Zusammenfassung 39 5 Ergebnisauswertung 40 5.1 Nachweis statistischer Eigenschaften 40 5.1.1 Stationarität, Leptokurtosis und Autokorrelation 40 5.1.2 Interpretation von Volatilität mittels GARCH–Prozess 44 5.1.3 Kritische Würdigung 47 5.2 Einfluss des Gewinns 47 5.2.1 Vorgehen 47 5.2.2 Ergebnisse 50 5.2.3 Kritische Würdigung 53 5.3 Ergebnisse der Koinzidenzanalyse 53 5.3.1 Vorgehen 53 5.3.2 Ergebnisse 56 5.3.3 Kritische Würdigung 58 6 Fazit 59
- Published
- 2015
364. Akzeptanz von einwohnerbezogenen Nahverkehrsabgaben zur Finanzierung des öffentlichen Personennahverkehrs: Bewertungsbedingungen von Grundbesitzabgabe und Bürgerticket am Beispiel Leipzig
- Author
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Seiler, Romy, Donner, Reik, Lämmer, Stefan, Nachtigall, Karl, and Technische Universität Dresden
- Subjects
ddc:380 ,public transport, acceptance, transportation fee, Leipzig ,Finanzierung öffentlicher Personennahverkehr, ÖPNV, Nahverkehrsabgabe, Grundbesitzabgabe, Bürgerticket, Leipzig, Akzeptanz, Drittnutzerfinanzierung - Abstract
Der öffentliche Personennahverkehr ist zunehmend von Finanzierungsproblemen bedroht, welche von Politik und Öffentlichkeit noch unterschätzt werden. Als Empfehlung für die zukünftige Sicherstellung finanzieller Mittel wird von Fachleuten zunehmend die Drittnutzerfinanzierung angeführt, welche über Nahverkehrsabgaben umgesetzt werden kann. Diese Arbeit beschäftigt sich genauer mit den einwohnerbezogenen Nahverkehrsabgaben der Grundbesitzabgabe und des Bürgertickets, da sie zur Zeit am meisten diskutiert bzw. als die Abgaben mit dem größten Umsetzungspotential gesehen werden. Da es sich hier um neue Finanzierungsinstrumente handelt, ist noch nicht genau klar, welche Akzeptanz dafür in der Gesellschaft vorhanden ist und von welchen Faktoren sie prädeterminiert wird. Sollen neue Abgaben eingeführt werden, so spielt jedoch das Wissen um die Akzeptanz in der Öffentlichkeit für die politischen Entscheidungsträger eine wesentliche Rolle. Es gibt jedoch zur Akzeptanz von Einwohnerabgaben bisher keine tiefgründigen Untersuchungen. Diese Arbeit möchte diese Forschungslücke schließen. Zu Beginn wird eine theoretische Grundlage geschaffen, indem Erfahrungen zur Akzeptanz anderer verkehrspolitischer Maßnahmen unter Berücksichtigung der spezifischen Charakteristik von Einwohnerabgaben auf die Akzeptanz von Grundbesitzabgabe und Bürgerticket übertragen werden. Um die realen Zusammenhänge zwischen Akzeptanz und deren Einflussfaktoren zu untersuchen, wurde eine (nichtrepräsentative) Online-Umfrage durchgeführt, welche sich auf die Stadt Leipzig bezog. Dazu wurden neben der Bewertung von Grundbesitzabgabe und Bürgerticket, welche als Indikatoren für die Akzeptanz verwendet wurden, die Faktoren Problembewusstsein, Zielvorstellungen, Verantwortungsattribution (für die Lösung von Verkehrsproblemen), Maßnahmenkenntnis, wahrgenommene Effektivität, Gerechtigkeit und Nutzen, sowie die Bewertung von drei Gestaltungsvariationen des Bürgertickets abgefragt. Es ergab sich ein Stichprobenumfang von n=393. Die Auswertung der Daten erfolgte mit Hilfe einer explorativen Faktorenanalyse und einer logistischen Regressionsanalyse mit dem Statistikprogramm R. Public transport is increasingly suffering from financial problems, and the severity of the situation seems to be underestimated by politics and the public. Experts suggest financial models that include third-party funds in addition to ticket revenue and municipality funding. This paper examines background and acceptance of two prominent models, a transportation fee based on real estate (“Grundbesitzabgabe”) and a fee based on residency (“Bürgerticket”). The real estate fee model leaves ticket prices unchanged but expands the public transportation network while the residency fee reduces ticket prices to zero. An online survey was conducted to assess acceptance and analyse potential determining factors for acceptance. The survey was limited to the city of Leipzig and yielded a sample size of n=393. The data was interpreted on the basis of explorative factor analysis and logistic regression.
- Published
- 2014
365. Network percolation provides early warnings of abrupt changes in coupled oscillatory systems: An explanatory analysis.
- Author
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Ehstand N, Donner RV, López C, and Hernández-García E
- Abstract
Functional networks are powerful tools to study statistical interdependency structures in spatially extended or multivariable systems. They have been used to get insights into the dynamics of complex systems in various areas of science. In particular, percolation properties of correlation networks have been employed to identify early warning signals of critical transitions. In this work, we further investigate the corresponding potential of percolation measures for the anticipation of different types of sudden shifts in the state of coupled irregularly oscillating systems. As a paradigmatic model system, we study the dynamics of a ring of diffusively coupled noisy FitzHugh-Nagumo oscillators and show that, when the oscillators are nearly completely synchronized, the percolation-based precursors successfully provide very early warnings of the rapid switches between the two states of the system. We clarify the mechanisms behind the percolation transition by separating global trends given by the mean-field behavior from the synchronization of individual stochastic fluctuations. We then apply the same methodology to real-world data of sea surface temperature anomalies during different phases of the El Niño-Southern Oscillation. This leads to a better understanding of the factors that make percolation precursors effective as early warning indicators of incipient El Niño and La Niña events.
- Published
- 2023
- Full Text
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366. Partial event coincidence analysis for distinguishing direct and indirect coupling in functional network construction.
- Author
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Lu J, Donner RV, Yin D, Guan S, and Zou Y
- Subjects
- Time Factors, Brain
- Abstract
Correctly identifying interaction patterns from multivariate time series presents an important step in functional network construction. In this context, the widespread use of bivariate statistical association measures often results in a false identification of links because strong similarity between two time series can also emerge without the presence of a direct interaction due to intermediate mediators or common drivers. In order to properly distinguish such direct and indirect links for the special case of event-like data, we present here a new generalization of event coincidence analysis to a partial version thereof, which is aimed at excluding possible transitive effects of indirect couplings. Using coupled chaotic systems and stochastic processes on two generic coupling topologies (star and chain configuration), we demonstrate that the proposed methodology allows for the correct identification of indirect interactions. Subsequently, we apply our partial event coincidence analysis to multi-channel EEG recordings to investigate possible differences in coordinated alpha band activity among macroscopic brain regions in resting states with eyes open (EO) and closed (EC) conditions. Specifically, we find that direct connections typically correspond to close spatial neighbors while indirect ones often reflect longer-distance connections mediated via other brain regions. In the EC state, connections in the frontal parts of the brain are enhanced as compared to the EO state, while the opposite applies to the posterior regions. In general, our approach leads to a significant reduction in the number of indirect connections and thereby contributes to a better understanding of the alpha band desynchronization phenomenon in the EO state.
- Published
- 2022
- Full Text
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367. Characteristic signatures of Northern Hemisphere blocking events in a Lagrangian flow network representation of the atmospheric circulation.
- Author
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Ehstand N, Donner RV, López C, and Hernández-García E
- Abstract
In the past few decades, boreal summers have been characterized by an increasing number of extreme weather events in the Northern Hemisphere extratropics, including persistent heat waves, droughts and heavy rainfall events with significant social, economic, and environmental impacts. Many of these events have been associated with the presence of anomalous large-scale atmospheric circulation patterns, in particular, persistent blocking situations, i.e., nearly stationary spatial patterns of air pressure. To contribute to a better understanding of the emergence and dynamical properties of such situations, we construct complex networks representing the atmospheric circulation based on Lagrangian trajectory data of passive tracers advected within the atmospheric flow. For these Lagrangian flow networks, we study the spatial patterns of selected node properties prior to, during, and after different atmospheric blocking events in Northern Hemisphere summer. We highlight the specific network characteristics associated with the sequence of strong blocking episodes over Europe during summer 2010 as an illustrative example. Our results demonstrate the ability of the node degree, entropy, and harmonic closeness centrality based on outgoing links to trace important spatiotemporal characteristics of atmospheric blocking events. In particular, all three measures capture the effective separation of the stationary pressure cell forming the blocking high from the normal westerly flow and the deviation of the main atmospheric currents around it. Our results suggest the utility of further exploiting the Lagrangian flow network approach to atmospheric circulation in future targeted diagnostic and prognostic studies.
- Published
- 2021
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368. Glossary on atmospheric electricity and its effects on biology.
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Fdez-Arroyabe P, Kourtidis K, Haldoupis C, Savoska S, Matthews J, Mir LM, Kassomenos P, Cifra M, Barbosa S, Chen X, Dragovic S, Consoulas C, Hunting ER, Robert D, van der Velde OA, Apollonio F, Odzimek A, Chilingarian A, Royé D, Mkrtchyan H, Price C, Bór J, Oikonomou C, Birsan MV, Crespo-Facorro B, Djordjevic M, Salcines C, López-Jiménez A, Donner RV, Vana M, Pedersen JOP, Vorenhout M, and Rycroft M
- Subjects
- Biology, Electricity
- Abstract
There is an increasing interest to study the interactions between atmospheric electrical parameters and living organisms at multiple scales. So far, relatively few studies have been published that focus on possible biological effects of atmospheric electric and magnetic fields. To foster future work in this area of multidisciplinary research, here we present a glossary of relevant terms. Its main purpose is to facilitate the process of learning and communication among the different scientific disciplines working on this topic. While some definitions come from existing sources, other concepts have been re-defined to better reflect the existing and emerging scientific needs of this multidisciplinary and transdisciplinary area of research.
- Published
- 2021
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369. Areawise significance tests for windowed recurrence network analysis.
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Lekscha J and Donner RV
- Abstract
Many time-series analysis techniques use sliding window approaches or are repeatedly applied over a continuous range of parameters. When combined with a significance test, intrinsic correlations among the pointwise analysis results can make falsely positive significant points appear as continuous patches rather than as isolated points. To account for this effect, we present an areawise significance test that identifies such false-positive patches. For this purpose, we numerically estimate the decorrelation length of the statistic of interest by calculating correlation functions between the analysis results and require an areawise significant point to belong to a patch of pointwise significant points that is larger than this decorrelation length. We apply our areawise test to results from windowed traditional and scale-specific recurrence network analysis in order to identify dynamical anomalies in time series of a non-stationary Rössler system and tree ring width index values from Eastern Canada. Especially, in the palaeoclimate context, the areawise testing approach markedly reduces the number of points that are identified as significant and therefore highlights only the most relevant features in the data. This provides a crucial step towards further establishing recurrence networks as a tool for palaeoclimate data analysis., Competing Interests: We declare we have no competing interests.
- Published
- 2019
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370. Network inference from the timing of events in coupled dynamical systems.
- Author
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Hassanibesheli F and Donner RV
- Abstract
Spreading phenomena like opinion formation or disease propagation often follow the links of some underlying network structure. While the effects of network topology on spreading efficiency have already been vastly studied, we here address the inverse problem of whether we can infer an unknown network structure from the timing of events observed at different nodes. For this purpose, we numerically investigate two types of event-based stochastic processes. On the one hand, a generic model of event propagation on networks is considered where the nodes exhibit two types of eventlike activity: spontaneous events reflecting mutually independent Poisson processes and triggered events that occur with a certain probability whenever one of the neighboring nodes exhibits any of these two kinds of events. On the other hand, we study a variant of the well-known SIRS model from epidemiology and record only the timings of state switching events of individual nodes, irrespective of the specific states involved. Based on simulations of both models on different prototypical network architectures, we study the pairwise statistical similarity between the sequences of event timings at all nodes by means of event synchronization and event coincidence analysis (ECA). By taking strong mutual similarities of event sequences (functional connectivity) as proxies for actual physical links (structural connectivity), we demonstrate that both approaches can lead to reasonable prediction accuracy. In general, sparser networks can be reconstructed more accurately than denser ones, especially in the case of larger networks. In such cases, ECA is shown to commonly exhibit the better reconstruction accuracy.
- Published
- 2019
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371. Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions.
- Author
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Kraemer KH, Donner RV, Heitzig J, and Marwan N
- Abstract
The appropriate selection of recurrence thresholds is a key problem in applications of recurrence quantification analysis and related methods across disciplines. Here, we discuss the distribution of pairwise distances between state vectors in the studied system's state space reconstructed by means of time-delay embedding as the key characteristic that should guide the corresponding choice for obtaining an adequate resolution of a recurrence plot. Specifically, we present an empirical description of the distance distribution, focusing on characteristic changes of its shape with increasing embedding dimension. Our results suggest that selecting the recurrence threshold according to a fixed percentile of this distribution reduces the dependence of recurrence characteristics on the embedding dimension in comparison with other commonly used threshold selection methods. Numerical investigations on some paradigmatic model systems with time-dependent parameters support these empirical findings.
- Published
- 2018
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372. Phase space reconstruction for non-uniformly sampled noisy time series.
- Author
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Lekscha J and Donner RV
- Abstract
Analyzing data from paleoclimate archives such as tree rings or lake sediments offers the opportunity of inferring information on past climate variability. Often, such data sets are univariate and a proper reconstruction of the system's higher-dimensional phase space can be crucial for further analyses. In this study, we systematically compare the methods of time delay embedding and differential embedding for phase space reconstruction. Differential embedding relates the system's higher-dimensional coordinates to the derivatives of the measured time series. For implementation, this requires robust and efficient algorithms to estimate derivatives from noisy and possibly non-uniformly sampled data. For this purpose, we consider several approaches: (i) central differences adapted to irregular sampling, (ii) a generalized version of discrete Legendre coordinates, and (iii) the concept of Moving Taylor Bayesian Regression. We evaluate the performance of differential and time delay embedding by studying two paradigmatic model systems-the Lorenz and the Rössler system. More precisely, we compare geometric properties of the reconstructed attractors to those of the original attractors by applying recurrence network analysis. Finally, we demonstrate the potential and the limitations of using the different phase space reconstruction methods in combination with windowed recurrence network analysis for inferring information about past climate variability. This is done by analyzing two well-studied paleoclimate data sets from Ecuador and Mexico. We find that studying the robustness of the results when varying the analysis parameters is an unavoidable step in order to make well-grounded statements on climate variability and to judge whether a data set is suitable for this kind of analysis.
- Published
- 2018
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373. A perturbation-theoretic approach to Lagrangian flow networks.
- Author
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Fujiwara N, Kirchen K, Donges JF, and Donner RV
- Abstract
Complex network approaches have been successfully applied for studying transport processes in complex systems ranging from road, railway, or airline infrastructures over industrial manufacturing to fluid dynamics. Here, we utilize a generic framework for describing the dynamics of geophysical flows such as ocean currents or atmospheric wind fields in terms of Lagrangian flow networks. In this approach, information on the passive advection of particles is transformed into a Markov chain based on transition probabilities of particles between the volume elements of a given partition of space for a fixed time step. We employ perturbation-theoretic methods to investigate the effects of modifications of transport processes in the underlying flow for three different problem classes: efficient absorption (corresponding to particle trapping or leaking), constant input of particles (with additional source terms modeling, e.g., localized contamination), and shifts of the steady state under probability mass conservation (as arising if the background flow is perturbed itself). Our results demonstrate that in all three cases, changes to the steady state solution can be analytically expressed in terms of the eigensystem of the unperturbed flow and the perturbation itself. These results are potentially relevant for developing more efficient strategies for coping with contaminations of fluid or gaseous media such as ocean and atmosphere by oil spills, radioactive substances, non-reactive chemicals, or volcanic aerosols.
- Published
- 2017
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374. Disentangling regular and chaotic motion in the standard map using complex network analysis of recurrences in phase space.
- Author
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Zou Y, Donner RV, Thiel M, and Kurths J
- Abstract
Recurrence in the phase space of complex systems is a well-studied phenomenon, which has provided deep insights into the nonlinear dynamics of such systems. For dissipative systems, characteristics based on recurrence plots have recently attracted much interest for discriminating qualitatively different types of dynamics in terms of measures of complexity, dynamical invariants, or even structural characteristics of the underlying attractor's geometry in phase space. Here, we demonstrate that the latter approach also provides a corresponding distinction between different co-existing dynamical regimes of the standard map, a paradigmatic example of a low-dimensional conservative system. Specifically, we show that the recently developed approach of recurrence network analysis provides potentially useful geometric characteristics distinguishing between regular and chaotic orbits. We find that chaotic orbits in an intermittent laminar phase (commonly referred to as sticky orbits) have a distinct geometric structure possibly differing in a subtle way from those of regular orbits, which is highlighted by different recurrence network properties obtained from relatively short time series. Thus, this approach can help discriminating regular orbits from laminar phases of chaotic ones, which presents a persistent challenge to many existing chaos detection techniques.
- Published
- 2016
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375. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package.
- Author
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Donges JF, Heitzig J, Beronov B, Wiedermann M, Runge J, Feng QY, Tupikina L, Stolbova V, Donner RV, Marwan N, Dijkstra HA, and Kurths J
- Subjects
- Stochastic Processes, Time Factors, Models, Theoretical, Nonlinear Dynamics, Software
- Abstract
We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.
- Published
- 2015
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376. Phase coherence and attractor geometry of chaotic electrochemical oscillators.
- Author
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Zou Y, Donner RV, Wickramasinghe M, Kiss IZ, Small M, and Kurths J
- Abstract
Chaotic attractors are known to often exhibit not only complex dynamics but also a complex geometry in phase space. In this work, we provide a detailed characterization of chaotic electrochemical oscillations obtained experimentally as well as numerically from a corresponding mathematical model. Power spectral density and recurrence time distributions reveal a considerable increase of dynamic complexity with increasing temperature of the system, resulting in a larger relative spread of the attractor in phase space. By allowing for feasible coordinate transformations, we demonstrate that the system, however, remains phase-coherent over the whole considered parameter range. This finding motivates a critical review of existing definitions of phase coherence that are exclusively based on dynamical characteristics and are thus potentially sensitive to projection effects in phase space. In contrast, referring to the attractor geometry, the gradual changes in some fundamental properties of the system commonly related to its phase coherence can be alternatively studied from a purely structural point of view. As a prospective example for a corresponding framework, recurrence network analysis widely avoids undesired projection effects that otherwise can lead to ambiguous results of some existing approaches to studying phase coherence. Our corresponding results demonstrate that since temperature increase induces more complex chaotic chemical reactions, the recurrence network properties describing attractor geometry also change gradually: the bimodality of the distribution of local clustering coefficients due to the attractor's band structure disappears, and the corresponding asymmetry of the distribution as well as the average path length increase.
- Published
- 2012
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377. Geometric and dynamic perspectives on phase-coherent and noncoherent chaos.
- Author
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Zou Y, Donner RV, and Kurths J
- Subjects
- Computer Simulation, Algorithms, Nonlinear Dynamics, Oscillometry methods
- Abstract
Statistically distinguishing between phase-coherent and noncoherent chaotic dynamics from time series is a contemporary problem in nonlinear sciences. In this work, we propose different measures based on recurrence properties of recorded trajectories, which characterize the underlying systems from both geometric and dynamic viewpoints. The potentials of the individual measures for discriminating phase-coherent and noncoherent chaotic oscillations are discussed. A detailed numerical analysis is performed for the chaotic Rössler system, which displays both types of chaos as one control parameter is varied, and the Mackey-Glass system as an example of a time-delay system with noncoherent chaos. Our results demonstrate that especially geometric measures from recurrence network analysis are well suited for tracing transitions between spiral- and screw-type chaos, a common route from phase-coherent to noncoherent chaos also found in other nonlinear oscillators. A detailed explanation of the observed behavior in terms of attractor geometry is given.
- Published
- 2012
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378. Identifying complex periodic windows in continuous-time dynamical systems using recurrence-based methods.
- Author
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Zou Y, Donner RV, Donges JF, Marwan N, and Kurths J
- Abstract
The identification of complex periodic windows in the two-dimensional parameter space of certain dynamical systems has recently attracted considerable interest. While for discrete systems, a discrimination between periodic and chaotic windows can be easily made based on the maximum Lyapunov exponent of the system, this remains a challenging task for continuous systems, especially if only short time series are available (e.g., in case of experimental data). In this work, we demonstrate that nonlinear measures based on recurrence plots obtained from such trajectories provide a practicable alternative for numerically detecting shrimps. Traditional diagonal line-based measures of recurrence quantification analysis as well as measures from complex network theory are shown to allow an excellent classification of periodic and chaotic behavior in parameter space. Using the well-studied Rössler system as a benchmark example, we find that the average path length and the clustering coefficient of the resulting recurrence networks are particularly powerful discriminatory statistics for the identification of complex periodic windows., (© 2010 American Institute of Physics.)
- Published
- 2010
- Full Text
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