Calorimeter clustering with minimal spanning treesWe present a top-down approach to calorimeter clustering. An algorithm based on minimal spanning tree theory is described briefly.G. Mavromanolakis·Sep 16, 2004SaveLearn
Statistics of transition times, phase diffusion and synchronization in periodically driven bistable systemsThe statistics of transitions between the metastable states of a periodically driven bistable Brownian oscillator are investigated on the basis of a two-state description by means of a master…Peter Talkner, Lukasz Machura, Michael Schindler et al.·Sep 14, 2004SaveLearn
Astumian's Paradox revisitedI give a simple analysis of the game that I previously published in Scientific American which shows the paradoxical behavior whereby two losing games randomly combine to form a winning game. The…R. Dean Astumian·Sep 3, 2004SaveLearn
A Method to Separate Stochastic and Deterministic Information from ElectrocardiogramsIn this work we present a new idea to develop a method to separate stochastic and deterministic information contained in an electrocardiogram, ECG, which may provide new sources of information with…R. M. Gutiérrez, L. Sandoval·Aug 31, 2004SaveLearn
The Astumian's ParadoxWe discuss some aspects of Astumian suggestions that combination of biased games (Parrondo's paradox) can explain performance of molecular motors. Unfortunately the model is flawed by explicit…Edward W. Piotrowski, Jan Sladkowski·Aug 27, 2004SaveLearn
Monte Carlo Calculation of the Single-Particle Spin-Echo Small-Angle Neutron Scattering Correlation FunctionA Monte Carlo algorithm for calculating the single-particle spin-echo small-angle neutron scattering (SESANS) correlation function is presented. It is argued that the algorithm provides a general and…H. Kaya·Aug 26, 2004SaveLearn
KDTREE 2: Fortran 95 and C++ software to efficiently search for near neighbors in a multi-dimensional Euclidean spaceMany data-based statistical algorithms require that one find near or nearest neighbors to a given vector among a set of points in that vector space, usually with Euclidean topology. The k-d…Matthew B. Kennel·Aug 16, 2004SaveLearn
On Bayesian Treatment of Systematic Uncertainties in Confidence Interval CalculationIn high energy physics, a widely used method to treat systematic uncertainties in confidence interval calculations is based on combining a frequentist construction of confidence belts with a Bayesian…Fredrik Tegenfeldt, Jan Conrad·Aug 8, 2004SaveLearn
Asymmetric Statistical ErrorsAsymmetric statistical errors arise for experimental results obtained by Maximum Likelihood estimation, in cases where the number of results is finite and the log likelihood function is not a…Roger Barlow·Jun 24, 2004SaveLearn
Maximum Entropy Multivariate Density Estimation: An exact goodness-of-fit approachWe consider the problem of estimating the population probability distribution given a finite set of multivariate samples, using the maximum entropy approach. In strict keeping with Jaynes'…Sabbir Rahman, Mahbub Majumdar·Jun 6, 2004SaveLearn
Formalism for obtaining nuclear momentum distributions by the Deep Inelastic Neutron Scattering techniqueWe present a new formalism to obtain momentum distributions in condensed matter from Neutron Compton Profiles measured by the Deep Inelastic Neutron Scattering technique. The formalism describes…J. J. Blostein, J. Dawidowski, J. R. Granada·Jun 4, 2004SaveLearn
Detecting non-linearities in data sets. Characterization of Fourier phase maps using the Weighted Scaling IndicesWe present a methodology for detecting non-linearities in data sets based on the characterization of the structural features of the Fourier phase maps. A Fourier phase map is a 2D set of points $M=…Roberto A. Monetti, Wolfram Bunk, Ferdinand Jamitzky et al.·May 25, 2004SaveLearn
Statistical Analysis for Long Term Correlations in the Stress Time Series of Jerky FlowStress time series from the PLC effect typically exhibit stick-slips of upload and download type. These data contain strong short-term correlations of a nonlinear type. We investigate whether there…Dimitris Kugiumtzis, Elias C. Aifantis·May 19, 2004SaveLearn
How many clusters? An information theoretic perspectiveClustering provides a common means of identifying structure in complex data, and there is renewed interest in clustering as a tool for the analysis of large data sets in many fields. A natural…Susanne Still, William Bialek·May 14, 2004SaveLearn
Remarks on statistical aspects of safety analysis of complex systemsWe analyze safety problems of complex systems using the methods of mathematical statistics for testing the output variables of a code simulating the operation of the system under consideration when…L. Pal, M. Makai·May 9, 2004SaveLearn
Extending Granger causality to nonlinear systemsWe consider extension of Granger causality to nonlinear bivariate time series. In this frame, if the prediction error of the first time series is reduced by including measurements from the second…Nicola Ancona, Daniele Marinazzo, Sebastiano Stramaglia·May 3, 2004SaveLearn
Goodness-of-fit tests in many dimensionsA method is presented to construct goodness-of-fit statistics in many dimensions for which the distribution of all possible test results in the limit of an infinite number of data becomes Gaussian if…A. van Hameren·May 3, 2004SaveLearn
Statistical properties of acoustic emission signals from metal cutting processesAcoustic Emission (AE) data from single point turning machining are analysed in this paper in order to gain a greater insight of the signal statistical properties for Tool Condition Monitoring (TCM)…F. A. Farrelly, A. Petri, L. Pitolli et al.·Apr 27, 2004SaveLearn
Asymmetric Uncertainties: Sources, Treatment and Potential DangersThe issue of asymmetric uncertainties resulting from fits, nonlinear propagation and systematic effects is reviewed. It is shown that, in all cases, whenever a published result is given with…G. D'Agostini·Apr 27, 2004SaveLearn
MaxEnt assisted MaxLik tomographyMaximum likelihood estimation is a valuable tool often applied to inverse problems in quantum theory. Estimation from small data sets can, however, have non unique solutions. We discuss this problem…J. Rehacek, Z. Hradil·Apr 26, 2004SaveLearn
Information and Covariance Matrices for Multivariate Burr III and Logistic distributionsMain result of this paper is to derive the exact analytical expressions of information and covariance matrices for multivariate Burr III and logistic distributions. These distributions arise as…Gholamhossein Yari, Ali Mohammad-Djafari·Apr 13, 2004SaveLearn
Entropy, Information Matrix and order statistics of Multivariate Pareto, Burr and related distributionsIn this paper we derive the exact analytical expressions for the information and covariance matrices of the multivariate Burr and related distributions. These distributions arise as tractable…Gholamhossein Yari, Ali Mohammad-Djafari·Apr 13, 2004SaveLearn
Techniques for noise removal from EEG, EOG and air flow signals in sleep patientsNoise is present in the wide variety of signals obtained from sleep patients. This noise comes from a number of sources, from presence of extraneous signals to adjustments in signal amplification and…Matthew J. Berryman, Sheila Messer, Andrew Allison et al.·Apr 7, 2004SaveLearn
Signal processing and statistical methods in analysis of text and DNAA number of signal processing and statistical methods can be used in analyzing either pieces of text or DNA sequences. These techniques can be used in a number of ways, such as determining authorship…Matthew J. Berryman, Andrew Allison, Pedro Carpena et al.·Apr 7, 2004SaveLearn
Increment definitions for scale dependent analysis of stochastic dataIt is common for scale-dependent analysis of stochastic data to use the increment Δ(t,r) = ξ(t+r) - ξ(t) of a data set ξ(t) as a stochastic measure, where r denotes the scale. For joint…Matthias Waechter, Alexei Kouzmitchev, Joachim Peinke·Apr 5, 2004SaveLearn