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Data Analysis papers — page 135

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A two-dimensional rough surface: Experiments on a pile of rice
Dynamical roughening of interfaces has received much attention in recent years. However, experiments have been restricted to one dimensional (1d) systems. Moreover, theoretical studies of the two…
C. M. Aegerter, R. Gunther, R. J. WijngaardenMay 7, 2002
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Computer simulations discussed in physical terms and terminology
As known, any numerical simulation is composed of two parts: (1) the initial part of writing the relevant code and (2) the running of this code on the computer screen. The second part of running the…
D. BarMay 6, 2002
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Decomposition of multicomponent mass spectra using Bayesian probability theory
We present a method for the decomposition of mass spectra of mixture gases using Bayesian probability theory. The method works without any calibration measurement and therefore applies also to the…
H. D. Kang, R. Preuss, T. Schwarz-Selinger et al.May 2, 2002
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Evolving Networks with Multi-species Nodes and Spread in the Number of Initial Links
We consider models for growing networks incorporating two effects not previously considered: (i) different species of nodes, with each species having different properties (such as different…
Jong-Won Kim, Brian Hunt, Edward OttMay 1, 2002
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Source separation as an exercise in logical induction
We examine the relationship between the Bayesian and information-theoretic formulations of source separation algorithms. This work makes use of the relationship between the work of Claude E. Shannon…
Kevin H. KnuthApr 25, 2002
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Inductive Logic: From Data Analysis to Experimental Design
In celebration of the work of Richard Threlkeld Cox, we explore inductive logic and its role in science touching on both experimental design and analysis of experimental results. In this exploration…
Kevin H. KnuthApr 23, 2002
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Vector- and tensor-valued descriptors for spatial patterns
Higher-rank Minkowski valuations are efficient means for describing the geometry and connectivity of spatial patterns. We show how to extend the framework of the scalar Minkowski valuations to…
Claus Beisbart, Robert Dahlke, Klaus Mecke et al.Mar 25, 2002
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Time series analysis for minority game simulations of financial markets
The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a…
Fernando F. Ferreira, Gerson Francisco, Birajara S. Machado et al.Mar 13, 2002
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Comment on "Indispensable Finite Time Correlations for Fokker-Planck Equations from Time Series Data"
Comment on "Indispensable Finite Time Correlations for Fokker-Planck Equations from Time Series Data"
R. Friedrich, Ch. Renner, M. Siefert et al.Mar 4, 2002
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Finding an Upper Limit in the Presence of Unknown Background
Experimenters report an upper limit if the signal they are trying to detect is non-existent or below their experiment's sensitivity. Such experiments may be contaminated with a background too…
S. YellinMar 1, 2002
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Multifractal detrended fluctuation analysis of nonstationary time series
We develop a method for the multifractal characterization of nonstationary time series, which is based on a generalization of the detrended fluctuation analysis (DFA). We relate our multifractal DFA…
Jan W. Kantelhardt, Stephan A. Zschiegner, Eva Koscielny-Bunde et al.Feb 27, 2002
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Products of Random Matrices
We derive analytic expressions for infinite products of random 2x2 matrices. The determinant of the target matrix is log-normally distributed, whereas the remainder is a surprisingly complicated…
A. D. Jackson, B. Lautrup, P. Johansen et al.Feb 12, 2002
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Mark correlations: relating physical properties to spatial distributions
Mark correlations provide a systematic approach to look at objects both distributed in space and bearing intrinsic information, for instance on physical properties. The interplay of the objects'…
Claus Beisbart, Martin Kerscher, Klaus MeckeJan 30, 2002
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Entropic Priors for Discrete Probabilistic Networks and for Mixtures of Gaussians Models
The ongoing unprecedented exponential explosion of available computing power, has radically transformed the methods of statistical inference. What used to be a small minority of statisticians…
Carlos C. RodriguezJan 9, 2002
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Entropy and inference, revisited
We study properties of popular near-uniform (Dirichlet) priors for learning undersampled probability distributions on discrete nonmetric spaces and show that they lead to disastrous results. However,…
Ilya Nemenman, Fariel Shafee, William BialekJan 9, 2002
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Statistical inference and modeling with the S distribution
We consider the problem of statistical inference for the S distribution and introduce new minimum distance estimators for the four parameters of the S distribution using Kolmogorov-Smirnov,…
Sergej V. Aksenov, Michael A. SavageauDec 17, 2001
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Similarity transformations approach for a generalized Fokker-Planck equation
By using similarity transformations approach, the exact propagator for a generalized one-dimensional Fokker-Planck equation, with linear drift force and space-time dependent diffusion coefficient, is…
F. Benamira, L. GuechiNov 30, 2001
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A Matlab Program to Calculate the Maximum Entropy Distributions
The classical Maximum Entropy (ME) problem consists of determining a probability distribution function (pdf) from a finite set of expectations of known functions. The solution depends on N+1…
A. Mohammad-DjafariNov 14, 2001
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A scale invariant Bayesian method to solve linear inverse problems
In this paper we propose a new Bayesian estimation method to solve linear inverse problems in signal and image restoration and reconstruction problems which has the property to be scale invariant. In…
A. Mohammad-Djafari, Jérôme IdierNov 14, 2001
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Scale Invariant Markov Models for Bayesian Inversion of Linear Inverse Problems
In a Bayesian approach for solving linear inverse problems one needs to specify the prior laws for calculation of the posterior law. A cost function can also be defined in order to have a common tool…
Stéphane Brette, Ali Mohammad-Djafari, Jérôme IdierNov 14, 2001
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A full Bayesian approach for inverse problems
The main object of this paper is to present some general concepts of Bayesian inference and more specifically the estimation of the hyperparameters in inverse problems. We consider a general linear…
A. Mohammad-DjafariNov 14, 2001
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A Comparison of Two Approaches: Maximum Entropy on the Mean (MEM) and Bayesian Estimation (BAYES) for Inverse Problems
To handle with inverse problems, two probabilistic approaches have been proposed: the maximum entropy on the mean (MEM) and the Bayesian estimation (BAYES). The main object of this presentation is to…
A. Mohammad-DjafariNov 14, 2001
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New Advances in Bayesian Calculation for Linear and Nonlinear Inverse Problems
The Bayesian approach has proved to be a coherent approach to handle ill posed Inverse problems. However, the Bayesian calculations need either an optimization or an integral calculation. The maximum…
A. Mohammad-DjafariNov 14, 2001
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A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections
Image reconstruction in X ray tomography consists in determining an object from its projections. In many applications such as non destructive testing, we look for an image who has a constant value…
A. Mohammad-DjafariNov 14, 2001
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A Bayesian Approach for the Determination of the Charge Density from Elastic Electron Scattering Data
The problem of the determination of the charge density from limited information about the charge form factor is an ill-posed inverse problem. A Bayesian probabilistic approach to this problem which…
A. Mohammad-Djafari, H. G. MillerNov 14, 2001
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