Fitting Power-laws in empirical data with estimators that work for all exponentsIt has been repeatedly stated that maximum likelihood (ML) estimates of exponents of power-law distributions can only be reliably obtained for exponents smaller than minus one. The main argument that…Rudolf Hanel, Bernat Corominas-Murtra, Bo Liu et al.·Sep 17, 2016SaveLearn
Mathematical Properties of Numerical Inversion for Jet CalibrationsNumerical inversion is a general detector calibration technique that is independent of the underlying spectrum. This procedure is formalized and important statistical properties are presented, using…Aviv Cukierman, Benjamin Nachman·Sep 16, 2016SaveLearn
Spatial Patterns of Wind Speed Distributions in SwitzerlandThis paper presents an initial exploration of high frequency records of extreme wind speed in two steps. The first consists in finding the suitable extreme distribution for 120 measuring stations…Mohamed Laib, Mikhail Kanevski·Sep 16, 2016SaveLearn
Practical Statistics for Particle PhysicistsThese three lectures provide an introduction to the main concepts of statistical data analysis useful for precision measurements and searches for new signals in High Energy Physics. The frequentist…Luca Lista·Sep 14, 2016SaveLearn
Estimation of presampling modulation transfer function in synchrotron radiation microtomographyThe spatial resolution achieved by recent synchrotron radiation microtomographs should be estimated from the modulation transfer function (MTF) on the micrometer scale. Step response functions of a…Ryuta Mizutani, Keisuke Taguchi, Akihisa Takeuchi et al.·Sep 8, 2016SaveLearn
A method for estimating spatial resolution of real image in the Fourier domainSpatial resolution is a fundamental parameter in structural sciences. In crystallography, the resolution is determined from the detection limit of high-angle diffraction in reciprocal space. In…Ryuta Mizutani, Rino Saiga, Susumu Takekoshi et al.·Sep 8, 2016SaveLearn
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality planeThe aim of this paper is to further explore the usefulness of the two-dimensional complexity-entropy causality plane as a texture image descriptor. A multiscale generalization is introduced in order…Luciano Zunino, Haroldo V. Ribeiro·Sep 6, 2016SaveLearn
Statistical properties of a filtered Poisson process with additive random noise: Distributions, correlations and moment estimationFiltered Poisson processes are often used as reference models for intermittent fluc- tuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive…Audun Theodorsen, Odd Erik Garcia, Martin Rypdal·Sep 6, 2016SaveLearn
The Waves and the Sigmas (To Say Nothing of the 750 GeV Mirage)This paper shows how p-values do not only create, as well known, wrong expectations in the case of flukes, but they might also dramatically diminish the `significance' of most likely genuine…Giulio D'Agostini·Sep 6, 2016SaveLearn
Scale-Bridging Model Development for Coal Particle DevolatilizationWhen performing large-scale, high-performance computations of multi-physics applications, it is common to limit the complexity of physics sub-models comprising the simulation. For a hierarchical…Benjamin B Schroeder, Sean T Smith, Philip J Smith et al.·Sep 3, 2016SaveLearn
Improved Inference for the Signal SignificanceWe study the properties of several likelihood-based statistics commonly used in testing for the presence of a known signal under a mixture model with known background, but unknown signal fraction.…Igor Volobouev, A. Alexandre Trindade·Sep 2, 2016SaveLearn
Go With the Flow, on Jupiter and Snow. Coherence From Model-Free Video Data without TrajectoriesViewing a data set such as the clouds of Jupiter, coherence is readily apparent to human observers, especially the Great Red Spot, but also other great storms and persistent structures. There are now…Abd AlRahman AlMomani, Erik M. Bollt·Aug 25, 2016SaveLearn
PALMA, an improved algorithm for DOSY signal processingNMR is a tool of choice for the measure of diffusion coefficients of species in solution. The DOSY experiment, a 2D implementation of this measure, has proven to be particularly useful for the study…Afef Cherni, Emilie Chouzenoux, Marc-André Delsuc·Aug 25, 2016SaveLearn
Inferring collective dynamical states from widely unobserved systemsWhen assessing spatially-extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of…Jens Wilting, Viola Priesemann·Aug 25, 2016SaveLearn
Reweighting with Boosted Decision TreesMachine learning tools are commonly used in modern high energy physics (HEP) experiments. Different models, such as boosted decision trees (BDT) and artificial neural networks (ANN), are widely used…A. Rogozhnikov·Aug 20, 2016SaveLearn
Improving randomness characterization through Bayesian model selectionNowadays random number generation plays an essential role in technology with important applications in areas ranging from cryptography, which lies at the core of current communication protocols, to…Rafael Díaz Hernández Rojas, Aldo Solís, Alí M. Angulo Martínez et al.·Aug 17, 2016SaveLearn
Van Vleck correction generalization for complex correlators with multilevel quantizationRemote sensing with phased antenna arrays is based on measurement of the cross-correlations between the signals from each antenna pair. Digital correlators have systematic errors due to the…L. V. Benkevitch, A. E. E. Rogers, C. J. Lonsdale et al.·Aug 15, 2016SaveLearn
Seeking Maximum Linearity of Transfer FunctionsLinearity is an important and frequently sought property in electronics and instrumentation. Here, we report a method capable of, given a transfer function, identifying the respective most linear…Filipi N. Silva, Cesar H. Comin, Luciano da F. Costa·Aug 13, 2016SaveLearn
Practical Statistics for Particle PhysicistsThese lectures introduce the basic ideas and practices of statistical analysis for particle physicists, using a real-world example to illustrate how the abstractions on which statistics is based are…Harrison B. Prosper·Aug 8, 2016SaveLearn
Online Decorrelation of Humidity and Temperature in Chemical Sensors for Continuous MonitoringA method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose…Ramon Huerta, Thiago S. Mosqueiro, Jordi Fonollosa et al.·Aug 4, 2016SaveLearn
FastDIRC: a fast Monte Carlo and reconstruction algorithm for DIRC detectorsFastDIRC is a novel fast Monte Carlo and reconstruction algorithm for DIRC detectors. A DIRC employs rectangular fused-silica bars both as Cherenkov radiators and as light guides. Cherenkov-photon…John Hardin, Mike Williams·Aug 2, 2016SaveLearn
Adaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian NoiseThis paper considers the general signal detection and parameter estimation problem in the presence of colored Gaussian noise disturbance. By modeling the disturbance with an autoregressive process,…Bo Tang, Haibo He, Steven Kay·Jul 27, 2016SaveLearn
Delineating Parameter Unidentifiabilities in Complex ModelsScientists use mathematical modelling to understand and predict the properties of complex physical systems. In highly parameterised models there often exist relationships between parameters over…Dhruva V. Raman, James Anderson, Antonis Papachristodoulou·Jul 26, 2016SaveLearn
Simultaneous Estimation of Noise Variance and Number of Peaks in Bayesian Spectral DeconvolutionThe heuristic identification of peaks from noisy complex spectra often leads to misunderstanding of the physical and chemical properties of matter. In this paper, we propose a framework based on…Satoru Tokuda, Kenji Nagata, Masato Okada·Jul 26, 2016SaveLearn
On the detection of superdiffusive behaviour in time seriesWe present a new method for detecting superdiffusive behaviour and for determining rates of superdiffusion in time series data. Our method applies equally to stochastic and deterministic time series…Georg A. Gottwald, Ian Melbourne·Jul 25, 2016SaveLearn