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9,300 | Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification | physics.data-an | Gaussian processes are a natural way of defining prior distributions over
functions of one or more input variables. In a simple nonparametric regression
problem, where such a function gives the mean of a Gaussian distribution for an
observed response, a Gaussian process model can easily be implemented using
matrix comp... | physics |
9,301 | The Analysis of Data from Continuous Probability Distributions | physics.data-an | Conventional statistics begins with a model, and assigns a likelihood of
obtaining any particular set of data. The opposite approach, beginning with the
data and assigning a likelihood to any particular model, is explored here for
the case of points drawn randomly from a continuous probability distribution. A
scalar fi... | physics |
9,302 | Objective Bayesian Statistics | physics.data-an | Bayesian inference --- although becoming popular in physics and chemistry ---
is hampered up to now by the vagueness of its notion of prior probability. Some
of its supporters argue that this vagueness is the unavoidable consequence of
the subjectivity of judgements --- even scientific ones. We argue that priors
can be... | physics |
9,303 | Experiments on Critical Phenomena in a Noisy Exit Problem | physics.data-an | We consider noise-driven exit from a domain of attraction in a
two-dimensional bistable system lacking detailed balance. Through analog and
digital stochastic simulations, we find a theoretically predicted bifurcation
of the most probable exit path as the parameters of the system are changed, and
a corresponding nonana... | physics |
9,304 | BAYES-LIN: An object-oriented environment for Bayes linear local computation | physics.data-an | BAYES-LIN is an extension of the LISP-STAT object-oriented statistical
computing environment, which adds to LISP-STAT some object prototypes
appropriate for carrying out local computation via message-passing between
clique-tree nodes of Bayes linear belief networks. Currently the BAYES-LIN
system represents a rather lo... | physics |
9,305 | Non-commutative time-frequency tomography | physics.data-an | The characterization of non-stationary signals requires joint time and
frequency information. However, time (t) and frequency (omega) being
non-commuting variables there cannot be a joint probability density in the
(t,omega) plane and the time-frequency distributions, that have been proposed,
have difficult interpretat... | physics |
9,306 | Characteristic functions and process identification by neural networks | physics.data-an | Principal component analysis (PCA) algorithms use neural networks to extract
the eigenvectors of the correlation matrix from the data. However, if the
process is non-Gaussian, PCA algorithms or their higher order generalisations
provide only incomplete or misleading information on the statistical properties
of the data... | physics |
9,307 | Cross Validated Non parametric Bayesianism by Markov Chain Monte Carlo | physics.data-an | Completely automatic and adaptive non-parametric inference is a pie in the
sky. The frequentist approach, best exemplified by the kernel estimators, has
excellent asymptotic characteristics but it is very sensitive to the choice of
smoothness parameters. On the other hand the Bayesian approach, best
exemplified by the ... | physics |
9,308 | Using projections and correlations to approximate probability distributions | physics.data-an | A method to approximate continuous multi-dimensional probability density
functions (PDFs) using their projections and correlations is described. The
method is particularly useful for event classification when estimates of
systematic uncertainties are required and for the application of an unbinned
maximum likelihood an... | physics |
9,309 | On the determination of probability density functions by using Neural Networks | physics.data-an | It is well known that the output of a Neural Network trained to disentangle
between two classes has a probabilistic interpretation in terms of the
a-posteriori Bayesian probability, provided that a unary representation is
taken for the output patterns. This fact is used to make Neural Networks
approximate probability d... | physics |
9,310 | Objections to the Unified Approach to the Computation of Classical Confidence Limits | physics.data-an | Conventional classical confidence intervals in specific cases are unphysical.
A solution to this problem has recently been published by Feldman and Cousins.
We show that there are cases where the new approach is not applicable and that
it does not remove the basic deficiencies of classical confidence limits. | physics |
9,311 | Estimating probability densities from short samples: a parametric maximum likelihood approach | physics.data-an | A parametric method similar to autoregressive spectral estimators is proposed
to determine the probability density function (pdf) of a random set. The method
proceeds by maximizing the likelihood of the pdf, yielding estimates that
perform equally well in the tails as in the bulk of the distribution. It is
therefore we... | physics |
9,312 | Depth Profile Reconstruction from Rutherford Backscattering Data | physics.data-an | An adaptive kernel method in the Bayesian framework together with a new
simulation program for Rutherford backscattering spectroscopy (RBS) have been
applied to the analysis of RBS data. Even in the case of strongly overlapping
RBS peaks a depth profile reconstruction without noise fitting has been
achieved. The adapti... | physics |
9,313 | The Signal Estimator Limit Setting Method | physics.data-an | A new method of background subtraction is presented which uses the concept of
a signal estimator to construct a confidence level which is always conservative
and which is never better than e^-s. The new method yields stronger exclusions
than the Bayesian method with a flat prior distribution. | physics |
9,314 | Improved Probability Method for Estimating Signal in the Presence of Background | physics.data-an | A suggestion is made for improving the Feldman Cousins method of estimating
signal counts in the presence of background. The method concentrates on finding
essential information about the signal and ignoring extraneous information
about background. An appropriate method is found which uses the condition that
the number... | physics |
9,315 | Anomalous jumping in a double-well potential | physics.data-an | Noise induced jumping between meta-stable states in a potential depends on
the structure of the noise. For an $\alpha$-stable noise, jumping triggered by
single extreme events contributes to the transition probability. This is also
called Levy flights and might be of importance in triggering sudden changes in
geophysic... | physics |
9,316 | Time Series Forecasting: A Multivariate Stochastic Approach | physics.data-an | This note deals with a multivariate stochastic approach to forecast the
behaviour of a cyclic time series. Particular attention is devoted to the
problem of the prediction of time behaviour of sunspot numbers for the current
23th cycle. The idea is to consider the previous known n cycles as n particular
realizations of... | physics |
9,317 | HEMAS: a Monte Carlo code for hadronic, electromagnetic and TeV muon components in air shower | physics.data-an | The features of the HEMAS code are presented. The results of the comparison
between the Monte Carlo expectation and the experimental data are shown. | physics |
9,318 | Definition of Nonequilibrium Entropy of General Systems | physics.data-an | The definition of nonequilibrium entropy is provided for the general
nonequilibrium processes by connecting thermodynamics with statistical physics,
and the principle of entropy increment in the nonequilibrium processes is also
proved in the paper. The result shows that the definition of nonequilibrium
entropy is not u... | physics |
9,319 | Analytic Confidence Level Calculations using the Likelihood Ratio and Fourier Transform | physics.data-an | The interpretation of new particle search results involves a confidence level
calculation on either the discovery hypothesis or the background-only ("null")
hypothesis. A typical approach uses toy Monte Carlo experiments to build an
expected experiment estimator distribution against which an observed
experiment's estim... | physics |
9,320 | Artificial Neural Network Modeling of Forest Tree Growth | physics.data-an | The problem of modeling forest tree growth curves with an artificial neural
network (NN) is examined. The NN parametric form is shown to be a suitable
model if each forest tree plot is assumed to consist of several differently
growing sub-plots. The predictive Bayesian approach is used in estimating the
NN output.
Da... | physics |
9,321 | When do finite sample effects significantly affect entropy estimates ? | physics.data-an | An expression is proposed for determining the error caused on entropy
estimates by finite sample effects. This expression is based on the Ansatz that
the ranked distribution of probabilities tends to follow an empirical Zipf law. | physics |
9,322 | Publication Bias (The "File-Drawer Problem") in Scientific Inference | physics.data-an | Publication bias arises whenever the probability that a study is published
depends on the statistical significance of its results. This bias, often called
the file-drawer effect since the unpublished results are imagined to be tucked
away in researchers' file cabinets, is potentially a severe impediment to
combining th... | physics |
9,323 | Mixtures of Gaussian process priors | physics.data-an | Nonparametric Bayesian approaches based on Gaussian processes have recently
become popular in the empirical learning community. They encompass many
classical methods of statistics, like Radial Basis Functions or various
splines, and are technically convenient because Gaussian integrals can be
calculated analytically. R... | physics |
9,324 | Kalman Filter Track Fits and Track Breakpoint Analysis | physics.data-an | We give an overview of track fitting using the Kalman filter method in the
NOMAD detector at CERN, and emphasize how the wealth of by-product information
can be used to analyze track breakpoints (discontinuities in track parameters
caused by scattering, decay, etc.). After reviewing how this information has
been previo... | physics |
9,325 | Application of Conditioning to the Gaussian-with-Boundary Problem in the Unified Approach to Confidence Intervals | physics.data-an | Roe and Woodroofe (RW) have suggested that certain conditional probabilities
be incorporated into the ``unified approach'' for constructing confidence
intervals, previously described by Feldman and Cousins (FC). RW illustrated
this conditioning technique using one of the two prototype problems in the FC
paper, that of ... | physics |
9,326 | The Equilibrium Distribution of Gas Molecules Adsorbed on an Active Surface | physics.data-an | We evaluate the exact equilibrium distribution of gas molecules adsorbed on
an active surface with an infinite number of attachment sites. Our result is a
Poisson distribution having mean $X = {\mu P P_s \over P_e}$, with $\mu$ the
mean gas density, $ P_s$ the sticking probability, $P_e$ the evaporation
probability in ... | physics |
9,327 | On mixing times for stratified walks on the d-cube | physics.data-an | Using the electric and coupling approaches, we derive a series of results
concerning the mixing times for the stratified random walk on the d-cube,
inspired in the results of Chung and Graham (1997) Stratified random walks on
the n-cube. | physics |
9,328 | XAFS spectroscopy. I. Extracting the fine structure from the absorption spectra | physics.data-an | Three independent techniques are used to separate fine structure from the
absorption spectra, the background function in which is approximated by (i)
smoothing spline. We propose a new reliable criterion for determination of
smoothing parameter and the method for raising of stability with respect to
k_min variation; (i... | physics |
9,329 | XAFS spectroscopy. II. Statistical evaluations in the fitting problems | physics.data-an | The problem of error analysis is addressed in stages beginning with the case
of uncorrelated parameters and proceeding to the Bayesian problem that takes
into account all possible correlations when a great deal of prior information
about the accessible parametr space is available. The formulas for the standard
deviatio... | physics |
9,330 | Tsallis' entropy maximization procedure revisited | physics.data-an | The proper way of averaging is an important question with regards to Tsallis'
Thermostatistics. Three different procedures have been thus far employed in the
pertinent literature. The third one, i.e., the Tsallis-Mendes-Plastino (TMP)
normalization procedure, exhibits clear advantages with respect to earlier
ones. In t... | physics |
9,331 | Singularities in kinetic theory | physics.data-an | It is revealed that distribution functions of practical gases relate to
singularities and such singularities can, with molecular motion, spread to the
entire region of interest. It is also shown that even common continuous
distribution functions involve a similar quasi-discontinuity difficulty. | physics |
9,332 | On the Confidence Interval for the parameter of Poisson Distribution | physics.data-an | The possibility of construction of continuous analogue of Poisson
distribution with the search of bounds of confidence intervals for parameter of
Poisson distribution is discussed. Also, in the article is shown that the true
value of a parameter of Poisson distribution for the observed value $\hat x$
has Gamma distribu... | physics |
9,333 | A Generalization of the Maximum Noise Fraction Transform | physics.data-an | A generalization of the maximum noise fraction (MNF) transform is proposed.
Powers of each band are included as new bands before the MNF transform is
performed. The generalized MNF (GMNF) is shown to perform better than the MNF
on a time dependent airborne electromagnetic (AEM) data filtering problem. | physics |
9,334 | Maximally Informative Statistics | physics.data-an | In this paper we propose a Bayesian, information theoretic approach to
dimensionality reduction. The approach is formulated as a variational principle
on mutual information, and seamlessly addresses the notions of sufficiency,
relevance, and representation. Maximally informative statistics are shown to
minimize a Kullb... | physics |
9,335 | Computer simulation approach to reliability and accuracy in EXAFS structural determinations | physics.data-an | The frequency distribution of different parameters of an EXAFS spectrum can
be directly sampled by analysing a population of simulated spectra produced by
adding computer-generated noise to a reference pattern. The procedure gives
statistical estimators of the parameter obtained with different data processing
strategie... | physics |
9,336 | Optimal Recovery of Local Truth | physics.data-an | Probability mass curves the data space with horizons. Let f be a multivariate
probability density function with continuous second order partial derivatives.
Consider the problem of estimating the true value of f(z) > 0 at a single point
z, from n independent observations. It is shown that, the fastest possible
estimato... | physics |
9,337 | Role and meaning of subjective probability: some comments on common misconceptions | physics.data-an | Criticisms of so called `subjective probability' come on the one hand from
those who maintain that probability in physics has only a frequentistic
interpretation, and, on the other, from those who tend to `objectivise'
Bayesian theory, arguing, e.g., that subjective probabilities are indeed based
`only on private intro... | physics |
9,338 | A Good Measure for Bayesian Inference | physics.data-an | The Gaussian theory of errors has been generalized to situations, where the
Gaussian distribution and, hence, the Gaussian rules of error propagation are
inadequate. The generalizations are based on Bayes' theorem and a suitable
measure. The following text sketches some chapters of a monograph that is
presently prepare... | physics |
9,339 | Complexity Through Nonextensivity | physics.data-an | The problem of defining and studying complexity of a time series has
interested people for years. In the context of dynamical systems, Grassberger
has suggested that a slow approach of the entropy to its extensive asymptotic
limit is a sign of complexity. We investigate this idea further by information
theoretic and st... | physics |
9,340 | Quantum Clustering | physics.data-an | We propose a novel clustering method that is based on physical intuition
derived from quantum mechanics. Starting with given data points, we construct a
scale-space probability function. Viewing the latter as the lowest eigenstate
of a Schrodinger equation, we use simple analytic operations to derive a
potential functi... | physics |
9,341 | Entropy and inference, revisited | physics.data-an | 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, an Occam-style phase space
argument expands the priors into their infinite mixture and resolves most of
the observed pro... | physics |
9,342 | Quasi-optimal observables: Attaining the quality of maximal likelihood in parameter estimation when only a MC event generator is available | physics.data-an | A new method of quasi-optimal observables allows one to approach the quality
of data processing usually associated with the method of maximal likelihood
within the simpler algorithmic context of generalized moments. | physics |
9,343 | On a quantitative method to analyse dynamical and measurement noise | physics.data-an | This letter reports on a new method of analysing experimentally gained time
series with respect to different types of noise involved, namely, we show that
it is possible to differentiate between dynamical and measurement noise. This
method does not depend on previous knowledge of model equations. For the
complicated ca... | physics |
9,344 | Characterization of a Low Frequency Power Spectral Density f^(-gamma) in a Threshold Model | physics.data-an | his study investigates the modifications of the thermal spectrum, at low
frequency, induced by an external damping on a system in heat contact with
internal fluctuating impurities. Those impurities can move among locations and
their oscillations are associated with a loss function depending on the model.
The fluctuatio... | physics |
9,345 | Reconstruction of dynamical equations for traffic flow | physics.data-an | Traffic flow data collected by an induction loop detector on the highway
close to Koeln-Nord are investigated with respect to their dynamics including
the stochastic content. In particular we present a new method, with which the
flow dynamics can be extracted directly from the measured data. As a result a
Langevin equa... | physics |
9,346 | Bayesian inference for inverse problems | physics.data-an | Traditionally, the MaxEnt workshops start by a tutorial day. This paper
summarizes my talk during 2001'th workshop at John Hopkins University. The main
idea in this talk is to show how the Bayesian inference can naturally give us
all the necessary tools we need to solve real inverse problems: starting by
simple inversi... | physics |
9,347 | Penalized maximum likelihood for multivariate Gaussian mixture | physics.data-an | In this paper, we first consider the parameter estimation of a multivariate
random process distribution using multivariate Gaussian mixture law. The labels
of the mixture are allowed to have a general probability law which gives the
possibility to modelize a temporal structure of the process under study. We
generalize ... | physics |
9,348 | Bayesian source separation with mixture of Gaussians prior for sources and Gaussian prior for mixture coefficients | physics.data-an | In this contribution, we present new algorithms to source separation for the
case of noisy instantaneous linear mixture, within the Bayesian statistical
framework. The source distribution prior is modeled by a mixture of Gaussians
[Moulines97] and the mixing matrix elements distributions by a Gaussian
[Djafari99a]. We ... | physics |
9,349 | Model selection for inverse problems: Best choice of basis functions and model order selection | physics.data-an | A complete solution for an inverse problem needs five main steps: choice of
basis functions for discretization, determination of the order of the model,
estimation of the hyperparameters, estimation of the solution, and finally,
characterization of the proposed solution. Many works have been done for the
three last ste... | physics |
9,350 | Entropy in Signal Processing (Entropie en Traitement du Signal) | physics.data-an | R\'esum\'e: Le principal objet de cette communication est de faire une
r\'etro perspective succincte de l'utilisation de l'entropie et du principe du
maximum d'entropie dans le domaine du traitement du signal. Apr\`es un bref
rappel de quelques d\'efinitions et du principe du maximum d'entropie, nous
verrons successive... | physics |
9,351 | Shape reconstruction in X-ray tomography from a small number of projections using deformable models | physics.data-an | X-ray tomographic image reconstruction consists of determining an object
function from its projections. In many applications such as non-destructive
testing, we look for a fault region (air) in a homogeneous, known background
(metal). The image reconstruction problem then becomes the determination of the
shape of the d... | physics |
9,352 | Probabilistic methods for data fusion | physics.data-an | The main object of this paper is to show how we can use classical
probabilistic methods such as Maximum Entropy (ME), maximum likelihood (ML)
and/or Bayesian (BAYES) approaches to do microscopic and macroscopic data
fusion. Actually ME can be used to assign a probability law to an unknown
quantity when we have macrosco... | physics |
9,353 | A Bayesian Approach for the Determination of the Charge Density from Elastic Electron Scattering Data | physics.data-an | 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 permits to take into
account both errors and prior information about the solution is presented. We
will show that many cla... | physics |
9,354 | A Bayesian Approach to Shape Reconstruction of a Compact Object from a Few Number of Projections | physics.data-an | 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 inside a region (default) and
another constant value outside that region (homogeneous region surrounding the
default). The ... | physics |
9,355 | New Advances in Bayesian Calculation for Linear and Nonlinear Inverse Problems | physics.data-an | 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 posteriori (MAP)
estimation requires the minimization of a compound criterion which, in general,
has two parts: a data... | physics |
9,356 | A Comparison of Two Approaches: Maximum Entropy on the Mean (MEM) and Bayesian Estimation (BAYES) for Inverse Problems | physics.data-an | 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 compare these two
approaches which are in fact two different inference procedures to define the
solution of an inverse p... | physics |
9,357 | A full Bayesian approach for inverse problems | physics.data-an | 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 situation where we are given
some data $\yb$ related to the unknown parameters $\xb$ by $\yb=\Ab \xb+\nb$
and where we can... | physics |
9,358 | Scale Invariant Markov Models for Bayesian Inversion of Linear Inverse Problems | physics.data-an | 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 for various Bayesian
estimators which depend on the data and the hyperparameters. The Gaussian case
excepted, these esti... | physics |
9,359 | A scale invariant Bayesian method to solve linear inverse problems | physics.data-an | 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 general, Bayesian estimators
are {\em nonlinear} functions of the observed data. The only exception is the
Gaussian case... | physics |
9,360 | A Matlab Program to Calculate the Maximum Entropy Distributions | physics.data-an | 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 $N+1$ Lagrange multipliers which are
determined by solving the set of nonlinear equations formed by the $N$ data
constraints and the ... | physics |
9,361 | Statistical inference and modeling with the S distribution | physics.data-an | 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, Cramer-von Mises and related distance
metrics. Approximate goodness-of-fit and confidence intervals for parameters
are calculated ... | physics |
9,362 | Entropic Priors for Discrete Probabilistic Networks and for Mixtures of Gaussians Models | physics.data-an | 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 advocating for the use of priors and a strict
adherence to bayes theorem, it is now becoming the norm across disciplines. The
ev... | physics |
9,363 | Comment on "Indispensable Finite Time Correlations for Fokker-Planck Equations from Time Series Data" | physics.data-an | Comment on "Indispensable Finite Time Correlations for Fokker-Planck
Equations from Time Series Data" | physics |
9,364 | Stochastic analysis of road surface roughness | physics.data-an | This paper was withdrawn by the authors due to significant new findings. A
new paper on the same topic has been submitted as physics/0310159. | physics |
9,365 | Evolving Networks with Multi-species Nodes and Spread in the Number of Initial Links | physics.data-an | 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 attachment probabilities to other node
species); and (ii) when a new node is born, its number of links to old nodes is
random with... | physics |
9,366 | Decomposition of multicomponent mass spectra using Bayesian probability theory | physics.data-an | 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 analysis of spectra containing
unstable species. For the example of mixtures of three different hydrocarbon
gases the algor... | physics |
9,367 | Computer simulations discussed in physical terms and terminology | physics.data-an | 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 program is extensively
discussed theoretically and technically in the relevant literature. In this
work we pay special at... | physics |
9,368 | A two-dimensional rough surface: Experiments on a pile of rice | physics.data-an | 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 dimensional (2d) case have
been highly inconclusive. Here we introduce an experimental 2d system, with
which the theories ca... | physics |
9,369 | Inference of entropies of discrete random variables with unknown cardinalities | physics.data-an | We examine the recently introduced NSB estimator of entropies of severely
undersampled discrete variables and devise a procedure for calculating the
involved integrals. We discover that the output of the estimator has a well
defined limit for large cardinalities of the variables being studied. Thus one
can estimate ent... | physics |
9,370 | The effects of related experiments | physics.data-an | The effects of the experiment itself upon the obtained results and,
especially, the influence of a large number of experiments are extensively
discussed in the literature. We show that the important factor that stands at
the basis of these effects is that the involved experiments are related and not
independent and det... | physics |
9,371 | Slow relaxation in weakly open vertex-splitting rational polygons | physics.data-an | The problem of splitting effects by vertex angles is discussed for
nonintegrable rational polygonal billiards. A statistical analysis of the decay
dynamics in weakly open polygons is given through the orbit survival
probability. Two distinct channels for the late-time relaxation of type
1/t^delta are established. The p... | physics |
9,372 | What is the true dropped calls rate when in the test it was found to be zero? | physics.data-an | We study the distributions of dropped calls rates for different wireless
(cellular) carriers in different markets. Our statistics comprises over 700
different market/carrier combinations. We find that the dropped calls rates
distribution is very close to lognormal. We derive an equation for the most
probable dropped ca... | physics |
9,373 | NeXus Software Status | physics.data-an | NeXus is a joint effort of both the synchrotron and neutron scattering
community to devlop a common data exchange format based on HDF. In order to
simplify access to NeXus-files a NeXus-API is provided. This NeXus-API has been
redesigned and expanded to cover both HDF versions 4 and 5. Only small changes
to the API wer... | physics |
9,374 | Parameter identification using the Hilbert transform | physics.data-an | Many physical systems can be adequately modelled using a second order
approximation. The problem of plant identification reduces to the problem of
estimating the position of a single pair of complex conjugate poles. One
approach to the problem is to apply the method of least squares to the time
domain data. This type o... | physics |
9,375 | GUI Tools for an Enhanced User Experience | physics.data-an | For instruments with many occasional users, it is important to have easy to
use software. To support the frequent users it is important to be flexible.
Using a scripting language to design a GUI and exposing it to the user allows
us to do both. We present our work on a GUI for reflectometry data analysis and
reduction ... | physics |
9,376 | The right tool for the job | physics.data-an | Tcl/tk provides for fast and flexible interface design but slow and
cumbersome vector processing. Octave provides fast and flexible vector
processing but slow and cumbersome interface design. Calling octave from tcl
gives you the flexibility to do a broad range of fast numerical manipulations
as part of an embedded GUI... | physics |
9,377 | Yet Another Analysis of Dice Problems | physics.data-an | During the MaxEnt 2002 workshop in Moscow, Idaho, Tony Vignaux asked again a
few simple questions about using Maximum Entropy or Bayesian approaches for the
famous Dice problems which have been analyzed many times through this workshop
and also in other places. Here, there is another analysis of these problems. I
hope ... | physics |
9,378 | MCMC joint separation and segmentation of hidden Markov fields | physics.data-an | In this contribution, we consider the problem of the blind separation of
noisy instantaneously mixed images. The images are modelized by hidden Markov
fields with unknown parameters. Given the observed images, we give a Bayesian
formulation and we propose to solve the resulting data augmentation problem by
implementing... | physics |
9,379 | Wavelet Domain Image Separation | physics.data-an | In this paper, we consider the problem of blind signal and image separation
using a sparse representation of the images in the wavelet domain. We consider
the problem in a Bayesian estimation framework using the fact that the
distribution of the wavelet coefficients of real world images can naturally be
modeled by an e... | physics |
9,380 | Fisher Information With Respect to Cumulants | physics.data-an | Fisher information is a measure of the best precision with which a parameter
can be estimated from statistical data. It can also be defined for a continuous
random variable without reference to any parameters, in which case it has a
physically compelling interpretation of representing the highest precision with
which t... | physics |
9,381 | Comment on "Including Systematic Uncertainties in Confidence Interval Construction for Poisson Statistics" | physics.data-an | The incorporation of systematic uncertainties into confidence interval
calculations has been addressed recently in a paper by Conrad et al. (Physical
Review D 67 (2003) 012002). In their work, systematic uncertainities in
detector efficiencies and background flux predictions were incorporated
following the hybrid frequ... | physics |
9,382 | Transient of the kinetic spherical model between two temperatures | physics.data-an | We solve the dynamic equation for the kinetic spherical model that initially
is in an arbitrary equilibrium state and then is left to evolve in a heat-bath
with another temperature. Flows of the Renormalizational group are determined. | physics |
9,383 | The power law character of off-site power failures | physics.data-an | A study on the behavior of off-site AC power failure recovery times at three
nuclear plant sites is presented. It is shown, that power law is appropriate
for the representation of failure frequency-duration correlation function of
off-site power failure events, based on simple assumptions about component
failure and re... | physics |
9,384 | Inference for bounded parameters | physics.data-an | The estimation of signal frequency count in the presence of background noise
has had much discussion in the recent physics literature, and Mandelkern [1]
brings the central issues to the statistical community, leading in turn to
extensive discussion by statisticians. The primary focus however in [1] and the
accompanyin... | physics |
9,385 | Internet websites statistics expressed in the framework of the Ursell-Mayer cluster formalism | physics.data-an | We show that it is possible to generalize the Ursell-Mayer cluster formalism
so that it may cover also the statistics of Internet websites. Our starting
point is the introduction of an extra variable that is assumed to take account,
as will be explained, of the nature of the Internet statistics. We then show,
following... | physics |
9,386 | Bayesian Inference in Processing Experimental Data: Principles and Basic Applications | physics.data-an | This report introduces general ideas and some basic methods of the Bayesian
probability theory applied to physics measurements. Our aim is to make the
reader familiar, through examples rather than rigorous formalism, with concepts
such as: model comparison (including the automatic Ockham's Razor filter
provided by the ... | physics |
9,387 | Multiscale Trend Analysis | physics.data-an | This paper introduces a multiscale analysis based on optimal piecewise linear
approximations of time series. An optimality criterion is formulated and on its
base a computationally effective algorithm is constructed for decomposition of
a time series into a hierarchy of trends (local linear approximations) at
different... | physics |
9,388 | Bayesian inference of nanoparticle-broadened x-ray line profiles | physics.data-an | A single and self-contained method for determining the crystallite-size
distribution and shape from experimental x-ray line profile data is presented.
We have shown that the crystallite-size distribution can be determined without
assuming a functional form for the size distribution, determining instead the
size distrib... | physics |
9,389 | Fitting a Sum of Exponentials to Numerical Data | physics.data-an | A finite sum of exponential functions may be expressed by a linear
combination of powers of the independent variable and by successive integrals
of the sum. This is proved for the general case and the connection between the
parameters in the sum and the coefficients in the linear combination is
highlighted. The fitting... | physics |
9,390 | Next-Generation EU DataGrid Data Management Services | physics.data-an | We describe the architecture and initial implementation of the
next-generation of Grid Data Management Middleware in the EU DataGrid (EDG)
project.
The new architecture stems out of our experience and the users requirements
gathered during the two years of running our initial set of Grid Data
Management Services. All... | physics |
9,391 | Go4 v2 Analysis Framework | physics.data-an | Go4 developed at GSI is an analysis framework with a general purpose non
blocking GUI. Go4 is based on ROOT. The GUI is implemented in Qt using GSI's
QtROOT interface. Analysis and GUI run in separate tasks communicating through
asynchronous object channels. A Go4 analysis may use any ROOT features. It can
be organized... | physics |
9,392 | Revison Control in the Grid Era - the unmet challenge | physics.data-an | As we move to distribute High Energy Physics computing tasks throughout the
global Grid, we are encountering ever more severe difficulties installing and
selecting appropriate versions of the supporting products. Problems show up at
every level: the base operating systems and tools, general purpose utilities
like root,... | physics |
9,393 | The full detector simulation for the Atlas experiment: status and outlook | physics.data-an | The simulation of the ATLAS detector is a major challenge, given the
complexity of the detector and the demanding environment of the LHC. The
apparatus, one of the biggest and most complex ever designed, requires a
detailed, flexible and, if possible, fast simulation which is needed already
today to deal with questions... | physics |
9,394 | Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at LHC | physics.data-an | The bremsstrahlung energy loss distribution of electrons propagating in
matter is highly non Gaussian. Because the Kalman filter relies solely on
Gaussian probability density functions, it might not be an optimal
reconstruction algorithm for electron tracks. A Gaussian-sum filter (GSF)
algorithm for electron track reco... | physics |
9,395 | CMS Data Analysis: Current Status and Future Strategy | physics.data-an | We present the current status of CMS data analysis architecture and describe
work on future Grid-based distributed analysis prototypes. CMS has two main
software frameworks related to data analysis: COBRA, the main framework, and
IGUANA, the interactive visualisation framework. Software using these
frameworks is used t... | physics |
9,396 | TPC tracking and particle identification in high-density environment | physics.data-an | Track finding and fitting algorithm in the ALICE Time projection chamber
(TPC) based on Kalman-filtering is presented. Implementation of particle
identification (PID) using d$E$/d$x$ measurement is discussed. Filtering and
PID algorithm is able to cope with non-Gaussian noise as well as with ambiguous
measurements in a... | physics |
9,397 | The PROOF Distributed Parallel Analysis Framework based on ROOT | physics.data-an | The development of the Parallel ROOT Facility, PROOF, enables a physicist to
analyze and understand much larger data sets on a shorter time scale. It makes
use of the inherent parallelism in event data and implements an architecture
that optimizes I/O and CPU utilization in heterogeneous clusters with
distributed stora... | physics |
9,398 | LCIO - A persistency framework for linear collider simulation studies | physics.data-an | Almost all groups involved in linear collider detector studies have their own
simulation software framework. Using a common persistency scheme would allow to
easily share results and compare reconstruction algorithms. We present such a
persistency framework, called LCIO (Linear Collider I/O). The framework has to
fulfi... | physics |
9,399 | The RooFit toolkit for data modeling | physics.data-an | RooFit is a library of C++ classes that facilitate data modeling in the ROOT
environment. Mathematical concepts such as variables, (probability density)
functions and integrals are represented as C++ objects. The package provides a
flexible framework for building complex fit models through classes that mimic
math opera... | physics |
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