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Luciano Zunino; Damián Gulich; Gustavo Funes; Darío G. Pérez
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We have experimentally confirmed the presence of longmemory correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. A laboratorycontrolled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing detrended...
Topics: Optics, Data Analysis, Statistics and Probability, Atmospheric and Oceanic Physics, Physics
Source: http://arxiv.org/abs/1507.01502
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M. Mert Ankaralı; Shahin Sefati; Manu S. Madhav; Andrew Long; Amy J. Bastian; Noah J. Cowan
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Many biological phenomena such as locomotion, circadian cycles, and breathing are rhythmic in nature and can be modeled as rhythmic dynamical systems. Dynamical systems modeling often involves neglecting certain characteristics of a physical system as a modeling convenience. For example, human locomotion is frequently treated as symmetric about the sagittal plane. In this work, we test this assumption by examining human walking dynamics around the steadystate (limitcycle). Here we adapt...
Topics: Physics, Mathematics, Data Analysis, Statistics and Probability, Dynamical Systems
Source: http://arxiv.org/abs/1407.8541
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A selection of unfolding methods commonly used in High Energy Physics is compared. The methods discussed here are: binbybin correction factors, matrix inversion, template fit, Tikhonov regularisation and two examples of iterative methods. Two procedures to choose the strength of the regularisation are tested, namely the Lcurve scan and a scan of global correlation coefficients. The advantages and disadvantages of the unfolding methods and choices of the regularisation strength are discussed...
Topics: Data Analysis, Statistics and Probability, Nuclear Experiment, Physics, High Energy Physics ...
Source: http://arxiv.org/abs/1611.01927
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Łukasz Rudnicki; Irene V. Toranzo; Pablo SanchezMoreno; Jesus S. Dehesa
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We introduce and discuss the notion of monotonicity for the complexity measures of general probability distributions, patterned after the resource theory of quantum entanglement. Then, we explore whether this property is satisfied by the three main intrinsic measures of complexity (CramerRao, FisherShannon, LMC) and some of their generalizations.
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1510.01547
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Barrett is a Python package for processing and visualising statistical inferences made using the nested sampling algorithm MultiNest. The main differential feature from competitors are full outofcore processing allowing barrett to handle arbitrarily large datasets. This is achieved by using the HDF5 data format.
Topics: Data Analysis, Statistics and Probability, Computation, Physics, Statistics
Source: http://arxiv.org/abs/1608.00990
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The Potts model was one of the most popular physics models of the twentieth century in an interdisciplinary context. It has been applied to a large variety of problems. Many generalizations exists and a whole range of models were inspired by this statistical physics tool. Here we present how a generic Potts model can be used to study complex data. As a demonstration, we engage our model in the analysis of night light patterns of human settlements observed on space photographs.
Topics: Applications, Physics, Physics and Society, Statistics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1501.04229
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György Steinbrecher; Giorgio Sonnino
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In many applications, the probability density function is subject to experimental errors. In this work the continuos dependence of a class of generalized entropies on the experimental errors is studied. This class includes the C. Shannon, C. Tsallis, A. R\'{e}nyi and generalized R\'{e}nyi entropies. By using the connection between R\'{e}nyi or Tsallis entropies, and the \textit{distance} in a the Lebesgue functional spaces, we introduce a further extensive generalizations of the R\'{e}nyi...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1603.06240
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Philipp Batz; Andreas Ruttor; Manfred Opper
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We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the FokkerPlanck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevintype equations and show how the method can be generalized to...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1603.01159
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Chuan Wen Loe; Henrik Jeldtoft Jensen
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MarkandRecapture is a methodology from Population Biology to estimate the number of a species without counting every individual. This is done by multiple samplings of the species using traps and discounting the instances that were caught repeated. In this paper we show that this methodology is applicable for citation analysis as it is also not feasible to count all the relevant publications of a research topic. In addition this estimation also allows us to propose a stopping rule for...
Topics: Physics and Society, Digital Libraries, Computing Research Repository, Data Analysis, Statistics...
Source: http://arxiv.org/abs/1503.06584
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Abderrahim Halimi; Nicolas Dobigeon; JeanYves Tourneret
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This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing accounting for endmember variability. The pixels are modeled by a linear combination of endmembers weighted by their corresponding abundances. However, the endmembers are assumed random to take into account their variability in the image. An additive noise is also considered in the proposed model generalizing the normal compositional model. The proposed algorithm exploits the whole image to provide spectral...
Topics: Physics, Data Analysis, Statistics and Probability, Applications, Statistics, Methodology
Source: http://arxiv.org/abs/1406.5071
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Claudia Battistin; John Hertz; Joanna Tyrcha; Yasser Roudi
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We propose a new algorithm for inferring the state of hidden spins and reconstructing the connections in a synchronous kinetic Ising model, given the observed history. Focusing on the case in which the hidden spins are conditionally independent of each other given the state of observable spins, we show that calculating the likelihood of the data can be simplified by introducing a set of replicated auxiliary spins. Belief Propagation (BP) and Susceptibility Propagation (SusP) can then be used to...
Topics: Statistical Mechanics, Data Analysis, Statistics and Probability, Physics, Disordered Systems and...
Source: http://arxiv.org/abs/1412.1727
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Cheng Xu; Chengqing Li; Jinhu Lü; Shi Shu
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This paper discusses the letter entitled "Network analysis of the state space of discrete dynamical systems" by A. Shreim et al. [Physical Review Letters, 98, 198701 (2007)]. We found that some theoretical analyses are wrong and the proposed indicators based on two parameters of the statemapping network cannot discriminate the dynamical complexity of the discrete dynamical systems composed of a 1D Cellular Automata.
Topics: Data Analysis, Statistics and Probability, Chaotic Dynamics, Nonlinear Sciences, Physics
Source: http://arxiv.org/abs/1611.06857
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Mariusz Tarnopolski
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The long range dependence of the fractional Brownian motion (fBm), fractional Gaussian noise (fGn), and differentiated fGn (DfGn) is described by the Hurst exponent $H$. Considering the realisations of these three processes as time series, they might be described by their statistical features, such as half of the ratio of the mean square successive difference to the variance, $\mathcal{A}$, and the number of turning points, $T$. This paper investigates the relationships between $\mathcal{A}$...
Topics: Mathematics, Nonlinear Sciences, Physics, Adaptation and SelfOrganizing Systems, Dynamical...
Source: http://arxiv.org/abs/1512.02928
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Laura Alessandretti; Márton Karsai; Laetitia Gauvin
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Multimodal transportation systems can be represented as timeresolved multilayer networks where different transportation modes connecting the same set of nodes are associated to distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geolocalised transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data....
Topics: Physics and Society, Social and Information Networks, Computing Research Repository, Data Analysis,...
Source: http://arxiv.org/abs/1509.08095
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Ardeshir M. Ebtehaj; Rafael L. Bras; Efi FoufoulaGeorgiou
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For precipitation retrievals over land, using satellite measurements in microwave bands, it is important to properly discriminate the weak rainfall signals from strong and highly variable background surface emission. Traditionally, land rainfall retrieval methods often rely on a weak signal of rainfall scattering on highfrequency channels (85 GHz) and make use of empirical thresholding and regressionbased techniques. Due to the increased ground surface signal interference, precipitation...
Topics: Atmospheric and Oceanic Physics, Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1503.05495
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Lei Le; Emilio Ferrara; Alessandro Flammini
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Information extracted from social media streams has been leveraged to forecast the outcome of a large number of realworld events, from political elections to stock market fluctuations. An increasing amount of studies demonstrates how the analysis of social media conversations provides cheap access to the wisdom of the crowd. However, extents and contexts in which such forecasting power can be effectively leveraged are still unverified at least in a systematic way. It is also unclear how...
Topics: Computing Research Repository, Data Analysis, Statistics and Probability, Learning, Physics,...
Source: http://arxiv.org/abs/1502.05886
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Jie Sun; Carlo Cafaro; Erik M. Bollt
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Inferring the coupling structure of complex systems from time series data in general by means of statistical and informationtheoretic techniques is a challenging problem in applied science. The reliability of statistical inferences requires the construction of suitable informationtheoretic measures that take into account both direct and indirect influences, manifest in the form of information flows, between the components within the system. In this work, we present an application of the...
Topics: Physics, Data Analysis, Statistics and Probability, Mathematics, Computing Research Repository,...
Source: http://arxiv.org/abs/1411.5350
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Sebastian Dorn; Torsten A. Enßlin
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Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations  matrices  acting on the data are often not accessible directly but are only represented indirectly in form of a computer routine. Such a routine implements the transformation a data vector undergoes under matrix multiplication. While efficient probing routines to estimate a matrix's diagonal or trace, based solely on such...
Topics: Methodology, Data Analysis, Statistics and Probability, Statistics, Instrumentation and Methods for...
Source: http://arxiv.org/abs/1504.02661
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Gaetana Spedalieri; Samuel L. Braunstein
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We consider the asymmetric formulation of quantum hypothesis testing, where two quantum hypotheses have different associated costs. In this problem, the aim is to minimize the probability of false negatives and the optimal performance is provided by the quantum Hoeffding bound. After a brief review of these notions, we show how this bound can be simplified for pure states. We then provide a general recipe for its computation in the case of multimode Gaussian states, also showing its connection...
Topics: Quantum Physics, Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1407.0884
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Maria Kalimeri; Vassilios Constantoudis; Constantinos Papadimitriou; Kostantinos Karamanos; Fotis K. Diakonos; Haris Papageorgiou
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We estimate the $n$gram entropies of natural language texts in wordlength representation and find that these are sensitive to text language and genre. We attribute this sensitivity to changes in the probability distribution of the lengths of single words and emphasize the crucial role of the uniformity of probabilities of having words with length between five and ten. Furthermore, comparison with the entropies of shuffled data reveals the impact of word length correlations on the estimated...
Topics: Physics, Data Analysis, Statistics and Probability, Computing Research Repository, Computation and...
Source: http://arxiv.org/abs/1401.4205
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Benjamin B Schroeder; Sean T Smith; Philip J Smith; Thomas H Fletcher; Andrew Packard; Michael Frenklach; Arun Hegde; Wenyu Li; James Oreluk
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When performing largescale, highperformance computations of multiphysics applications, it is common to limit the complexity of physics submodels comprising the simulation. For a hierarchical system of coal boiler simulations a scalebridging model is constructed to capture characteristics appropriate for the applicationscale from a detailed coal devolatilization model. Such scalebridging allows full descriptions of scaleapplicable physics, while functioning at reasonable computational...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1609.00871
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Marie Farge; Kai Schneider
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Wavelet analysis and compression tools are reviewed and different applications to study MHD and plasma turbulence are presented. We introduce the continuous and the orthogonal wavelet transform and detail several statistical diagnostics based on the wavelet coefficients. We then show how to extract coherent structures out of fully developed turbulent flows using waveletbased denoising. Finally some multiscale numerical simulation schemes using wavelets are described. Several examples for...
Topics: Computational Physics, Nonlinear Sciences, Data Analysis, Statistics and Probability, Physics,...
Source: http://arxiv.org/abs/1508.05650
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Bertrand M. Roehner
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The monthly pattern of suicides has remained a puzzle ever since it was discovered in the second half of the 19th century. In this paper we intend to "explain" not the pattern itself but rather its changes across countries and in the course of time. First, we show that the fairly common idea according to which this pattern is decaying in "modern" societies is not altogether true. For instance, around 2000, in well urbanized countries like South Korea or Spain this pattern...
Topics: Physics, Data Analysis, Statistics and Probability, Physics and Society
Source: http://arxiv.org/abs/1408.5242
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It is shown that whenever the multiplicative normalization of a fitting function is not known, least square fitting by $\chi^2$ minimization can be performed with one parameter less than usual by converting the normalization parameter into a function of the remaining parameters and the data.
Topics: Computational Physics, Data Analysis, Statistics and Probability, Statistical Mechanics, Physics,...
Source: http://arxiv.org/abs/1505.07564
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Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing...
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1501.03548
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Christian Kleiber
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Methods for detecting structural changes, or change points, in time series data are widely used in many fields of science and engineering. This chapter sketches some basic methods for the analysis of structural changes in time series data. The exposition is confined to retrospective methods for univariate time series. Several recent methods for dating structural changes are compared using a time series of oil prices spanning more than 60 years. The methods broadly agree for the first part of...
Topics: Physics, Quantitative Finance, Statistical Finance, Data Analysis, Statistics and Probability,...
Source: http://arxiv.org/abs/1702.06913
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Andrzej Kulig; Jaroslaw Kwapien; Tomasz Stanisz; Stanislaw Drozdz
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From a grammar point of view, the role of punctuation marks in a sentence is formally defined and well understood. In semantic analysis punctuation plays also a crucial role as a method of avoiding ambiguity of the meaning. A different situation can be observed in the statistical analyses of language samples, where the decision on whether the punctuation marks should be considered or should be neglected is seen rather as arbitrary and at present it belongs to a researcher's preference. An...
Topics: Data Analysis, Statistics and Probability, Computation and Language, Computing Research Repository,...
Source: http://arxiv.org/abs/1604.00834
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Robert W. Johnson
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The algorithm AMGKQ for adaptive multivariate GaussKronrod quadrature over hyperrectangular regions of arbitrary dimensionality is proposed and implemented in Octave/MATLAB. It can approximate numerically any number of integrals over a common domain simultaneously. Improper integrals are addressed through singularity weakening coordinate transformations. Internal singularities are addressed through the use of breakpoints. Its accuracy performance is investigated thoroughly, and its running...
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1410.1064
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Navid Dianati; Nima Dehmamy
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Many real world networks, such as social networks, are primarily formed through local interactions between agents. Additionally, in contrast with common network models, social and biological networks exhibit a high degree of clustering. Here we construct a class of network growth models based on local interactions on a metric space, capable of producing arbitrary degree distributions as well as a naturally high degree of clustering akin to biological networks. As a specific example, we study...
Topics: Condensed Matter, Data Analysis, Statistics and Probability, Physics, Statistical Mechanics,...
Source: http://arxiv.org/abs/1501.03543
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Rober Jankowski; Marcin Makowski; Edward W. Piotrowski
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We present a new method of estimating the dispersion of a distribution which is based on the surprising property of a function that measures information processing intensity. It turns out that this function has a maximum at its fixed point. We use a fixedpoint equation to estimate the parameter of the distribution that is of interest to us. We illustrate the estimation method by using the example of an exponential distribution. The codes of programs that calculate the experimental values of...
Topics: Physics, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1404.0262
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Michael Tsyrulnikov; Alexander Rakitko
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A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the modelerror and predictabilityerror covariance matrices. The latter are treated as random matrices and updated in a hierarchical Bayes scheme along with the state. The (hyper)prior distribution of the covariance matrices is assumed to be inverse Wishart. The new Hierarchical Bayes Ensemble Filter (HBEF)...
Topics: Data Analysis, Statistics and Probability, Atmospheric and Oceanic Physics, Physics
Source: http://arxiv.org/abs/1509.00652
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A. Z. Gorski; M. Stroz; P. Oswiecimka; J. Skrzat
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The boxcounting (BC) algorithm is applied to calculate fractal dimensions of four fractal sets. The sets are contaminated with an additive noise with amplitude $\gamma = 10^{5} \div 10^{1}$. The accuracy of calculated numerical values of the fractal dimensions is analyzed as a function of $\gamma$ for different sizes of the data sample ($n_{tot}$). In particular, it has been found that a tiny ($10^{5}$) addition of noise generates much larger (three orders of magnitude) error of the...
Topics: Physics, Data Analysis, Statistics and Probability, Nonlinear Sciences, Adaptation and...
Source: http://arxiv.org/abs/1412.6664
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M. E. J. Newman; Aaron Clauset
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For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network, geographic location of nodes in the Internet, or cellular function of nodes in a gene regulatory network. Here we demonstrate how this "metadata" can be used to improve our analysis and understanding of network structure. We focus in particular on the problem of community detection in networks and...
Topics: Social and Information Networks, Data Analysis, Statistics and Probability, Physics and Society,...
Source: http://arxiv.org/abs/1507.04001
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Galen Wilkerson; Ramin Khalili; Stefan Schmid
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Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper attempts to complement this research by looking at a categoryrich mobility data set. In order to shed light on the impact of categories, as a case study, we use conventionally collected German mobility data. In contrast to `checkin'based data, our results are...
Topics: Physics, Data Analysis, Statistics and Probability, Applications, Statistics, Computers and...
Source: http://arxiv.org/abs/1401.0207
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Oleguer Sagarra; Mario GutiérrezRoig; Isabelle Bonhoure; Josep Perelló
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Under the name of Citizen Science, many innovative practices in which volunteers partner with scientist to pose and answer realworld questions are quickly growing worldwide. Citizen Science can furnish ready made solutions with the active role of citizens. However, this framework is still far from being well stablished to become a standard tool for Computational Social Sciences research. We present our experience in bridging Computational Social Sciences with Citizen Science philosophy, which...
Topics: Data Analysis, Statistics and Probability, Computing Research Repository, Physics and Society,...
Source: http://arxiv.org/abs/1509.06575
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Petr Jizba; Jan Korbel
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In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal binwidth in histograms generated from underlying probability distributions of interest. The method presented uses techniques of R\'{e}nyi's entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In...
Topics: Physics, Data Analysis, Statistics and Probability, Mathematics, Statistical Finance, Quantitative...
Source: http://arxiv.org/abs/1401.3316
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Takuya Iwata; Ken Umeno
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We can observe the changes of Total Electron Content, TEC, in ionosphere by analyzing the data from GNSS satellites. There are many reports about TEC anomalies after earthquakes, i.e. large earthquakes often disturb the ionosphere. Up to now, preseismic TEC anomalies have been reported in several papers. However, they are not so clear as coseismic TEC anomalies, and their analysis methods have some problems for practical earthquake prediction. One factor making it difficult to detect TEC...
Topics: Data Analysis, Statistics and Probability, Geophysics, Chaotic Dynamics, Nonlinear Sciences, Physics
Source: http://arxiv.org/abs/1606.02708
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Shuyang Gao; Greg Ver Steeg; Aram Galstyan
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Estimating mutual information (MI) from samples is a fundamental problem in statistics, machine learning, and data analysis. Recently it was shown that a popular class of nonparametric MI estimators perform very poorly for strongly dependent variables and have sample complexity that scales exponentially with the true MI. This undesired behavior was attributed to the reliance of those estimators on local uniformity of the underlying (and unknown) probability density function. Here we present a...
Topics: Information Theory, Data Analysis, Statistics and Probability, Computing Research Repository,...
Source: http://arxiv.org/abs/1508.00536
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KajKolja Kleineberg; Dirk Helbing
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Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However,...
Topics: Nonlinear Sciences, Computational Physics, Data Analysis, Statistics and Probability, Physics,...
Source: http://arxiv.org/abs/1611.04395
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Alessandro Bessi; Guido Caldarelli; Michela Del Vicario; Antonio Scala; Walter Quattrociocchi
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Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories  e.g. global warming induced by chemtrails or the link between vaccines and autism  find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of...
Topics: Physics, Data Analysis, Statistics and Probability, Computers and Society, Computing Research...
Source: http://arxiv.org/abs/1409.2651
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Emmanuel Busato; David Calvet; Timothée TheveneauxPelzer
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A software tool, computing observed and expected upper limits on poissonian process rates using a hybrid frequentistbayesian CLs method, is presented. This tool can be used for simple counting experiments where only signal, background and observed yields are provided or for multibin experiments where binned distributions of discriminating variables are provided. It allows to combine several channels and takes into account statistical and systematic uncertainties, as well as correlations of...
Topics: Physics, High Energy Physics  Experiment, Data Analysis, Statistics and Probability
Source: http://arxiv.org/abs/1502.02610
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Marco A. Amaral; Jafferson K. L. da Silva; Lucas Wardil
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Evolutionary game theory is a common framework to study the evolution of cooperation, where it is usually assumed that the same game is played in all interactions. Here, we investigate a model where the game that is played by two individuals is uniformly drawn from a sample of two different games. Using the master equation approach we show that the random mixture of two games is equivalent to play the average game when (i) the strategies are statistically independent of the game distribution...
Topics: Biological Physics, Physics and Society, Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1505.03875
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Niall M. Mangan; J. Nathan Kutz; Steven L. Brunton; Joshua L. Proctor
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We develop an algorithm for model selection which allows for the consideration of a combinatorially large number of candidate models governing a dynamical system. The innovation circumvents a disadvantage of standard model selection which typically limits the number candidate models considered due to the intractability of computing information criteria. Using a recently developed sparse identification of nonlinear dynamics algorithm, the subselection of candidate models near the Pareto...
Topics: Physics, Data Analysis, Statistics and Probability, Chaotic Dynamics, Nonlinear Sciences
Source: http://arxiv.org/abs/1701.01773
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Sophie A. Murray; Suzy Bingham; Michael Sharpe; David R. Jackson
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The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms; forecasts for each active region on the solar disk over the next 24 hours, and fulldisk forecasts for the next four days. Here the forecasting process is described in detail, as well as first verification...
Topics: Physics, Solar and Stellar Astrophysics, Data Analysis, Statistics and Probability, Astrophysics,...
Source: http://arxiv.org/abs/1703.06754
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Jessica Lovelace Rainbolt; Michael Schmitt
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Minimal spanning trees (MSTs) have been used in cosmology and astronomy to distinguish distributions of points in a multidimensional space. They are essentially unknown in particle physics, however. We briefly define MSTs and illustrate their properties through a series of examples. We show how they might be applied to study a typical event sample from a collider experiment and conclude that MSTs may prove useful in distinguishing different classes of events.
Topics: High Energy Physics  Experiment, Data Analysis, Statistics and Probability, Applications, Physics,...
Source: http://arxiv.org/abs/1608.04772
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Bahram Houchmandzadeh
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The LuriaDelbr{\"u}ck experiment is a cornerstone of evolutionary theory, demonstrating the randomness of mutations before selection. The distribution of the number of mutants in this experiment has been the subject of intense investigation during the last 70 years. Despite this considerable effort, most of the results have been obtained under the assumption of constant growth rate, which is far from the experimental condition. We derive here the properties of this distribution for...
Topics: Biological Physics, Data Analysis, Statistics and Probability, Populations and Evolution,...
Source: http://arxiv.org/abs/1505.06108
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ChenYun Lin; Arin Minasian; Xin Jessica Qi; HauTieng Wu
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We extensively study the rotational group structure inside the patch space by introducing the fiber bundle structure. The rotational group structure leads to a new image denoising algorithm called the \textit{vector nonlocal Euclidean median} (VNLEM). The theoretical aspect of VNLEM is studied, which explains why the VNLEM and traditional nonlocal mean/nonlocal Euclidean median (NLEM) algorithm work. The numerical issue of the VNLEM is improved by taking the orientation feature in the...
Topics: Data Analysis, Statistics and Probability, Physics
Source: http://arxiv.org/abs/1611.05073
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Kolmogorov's first axiom of probability is probability takes values between 0 and 1; however, in Cox's derivation of probability having a maximum value of unity is arbitrary since he derives probability as a tool to rank degrees of plausibility. Probability can then be used to make inferences in instances of incomplete information, which is the foundation of Baysian probability theory. This article formulates a rule, which if obeyed, allows probability to take complex values and still be...
Topics: Data Analysis, Statistics and Probability, Probability, Quantum Physics, Physics, Mathematics
Source: http://arxiv.org/abs/1612.00494
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Enrico Maiorino; Filippo Maria Bianchi; Lorenzo Livi; Antonello Rizzi; Alireza Sadeghian
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In this paper, we propose a novel datadriven approach for removing trends (detrending) from nonstationary, fractal and multifractal time series. We consider realvalued time series relative to measurements of an underlying dynamical system that evolves through time. We assume that such a dynamical process is predictable to a certain degree by means of a class of recurrent networks called Echo State Network (ESN), which are capable to model a generic dynamical process. In order to isolate the...
Topics: Learning, Neural and Evolutionary Computing, Data Analysis, Statistics and Probability, Computing...
Source: http://arxiv.org/abs/1510.07146
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A. Hadjihosseini; J. Peinke; N. P. Hoffmann
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This work presents an analysis of ocean wave data including rogue waves. A stochastic approach based on the theory of Markov processes is applied. With this analysis we achieve a characterization of the scale dependent complexity of ocean waves by means of a FokkerPlanck equation, providing stochastic information of multiscale processes. In particular we show evidence of Markov properties for increment processes, which means that a three point closure for the complexity of the wave structures...
Topics: Physics, Data Analysis, Statistics and Probability, Atmospheric and Oceanic Physics
Source: http://arxiv.org/abs/1402.4366