Search results for "binary [neutron star]"

showing 10 items of 544 documents

Explicit, identical maximum likelihood estimates for some cyclic Gaussian and cyclic Ising models

2017

Cyclic models are a subclass of graphical Markov models with simple, undirected probability graphs that are chordless cycles. In general, all currently known distributions require iterative procedures to obtain maximum likelihood estimates in such cyclic models. For exponential families, the relevant conditional independence constraint for a variable pair is given all remaining variables, and it is captured by vanishing canonical parameters involving this pair. For Gaussian models, the canonical parameter is a concentration, that is, an off-diagonal element in the inverse covariance matrix, while for Ising models, it is a conditional log-linear, two-factor interaction. We give conditions un…

Statistics and ProbabilityGaussianBinary numberMarkov modelCombinatoricsConstraint (information theory)symbols.namesakeExponential familyConditional independencesymbolsApplied mathematicsIsing modelStatistics Probability and UncertaintyVariable (mathematics)MathematicsStat
researchProduct

Local bandwidth selection for kernel density estimation in a bifurcating Markov chain model

2020

International audience; We propose an adaptive estimator for the stationary distribution of a bifurcating Markov Chain onRd. Bifurcating Markov chains (BMC for short) are a class of stochastic processes indexed by regular binary trees. A kernel estimator is proposed whose bandwidths are selected by a method inspired by the works of Goldenshluger and Lepski [(2011), 'Bandwidth Selection in Kernel Density Estimation: Oracle Inequalities and Adaptive Minimax Optimality',The Annals of Statistics3: 1608-1632). Drawing inspiration from dimension jump methods for model selection, we also provide an algorithm to select the best constant in the penalty. Finally, we investigate the performance of the…

Statistics and ProbabilityKernel density estimationadaptive estimationNonparametric kernel estimation01 natural sciences010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0502 economics and businessbinary treesApplied mathematicsbifurcating autoregressive processes0101 mathematics[MATH]Mathematics [math]050205 econometrics MathematicsBinary treeStationary distributionMarkov chainStochastic processModel selection05 social sciencesEstimator[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Adaptive estimatorStatistics Probability and UncertaintyGoldenshluger-Lepski methodology
researchProduct

A generalization of the inhomogeneity measure for point distributions to the case of finite size objects

2008

The statistical measure of spatial inhomogeneity for n points placed in chi cells each of size kxk is generalized to incorporate finite size objects like black pixels for binary patterns of size LxL. As a function of length scale k, the measure is modified in such a way that it relates to the smallest realizable value for each considered scale. To overcome the limitation of pattern partitions to scales with k being integer divisors of L we use a sliding cell-sampling approach. For given patterns, particularly in the case of clusters polydispersed in size, the comparison between the statistical measure and the entropic one reveals differences in detection of the first peak while at other sca…

Statistics and ProbabilityLength scalePlanarStatistical Mechanics (cond-mat.stat-mech)PixelMathematical analysisFOS: Physical sciencesBinary numberGeometryCondensed Matter PhysicsCondensed Matter - Statistical MechanicsUniversality (dynamical systems)MathematicsPhysica A: Statistical Mechanics and its Applications
researchProduct

A matrix-valued Bernoulli distribution

2006

AbstractMatrix-valued distributions are used in continuous multivariate analysis to model sample data matrices of continuous measurements; their use seems to be neglected for binary, or more generally categorical, data. In this paper we propose a matrix-valued Bernoulli distribution, based on the log-linear representation introduced by Cox [The analysis of multivariate binary data, Appl. Statist. 21 (1972) 113–120] for the Multivariate Bernoulli distribution with correlated components.

Statistics and ProbabilityNumerical AnalysisDISCRETEMODELSMatrix t-distributionMultivariate normal distributionMatrix-valued distributionsBINARYNormal-Wishart distributionBinomial distributionBernoulli distributionCategorical distributionStatisticsApplied mathematicsBernoulli processStatistics Probability and UncertaintyCorrelated multivariate binary responsesMathematicsMultivariate stable distributionMultivariate Bernoulli distributionJournal of Multivariate Analysis
researchProduct

A dynamical approach to compatible and incompatible questions

2019

We propose a natural strategy to deal with compatible and incompatible binary questions, and with their time evolution. The strategy is based on the simplest, non-commutative, Hilbert space $\mathcal{H}=\mathbb{C}^2$, and on the (commuting or not) operators on it. As in ordinary Quantum Mechanics, the dynamics is driven by a suitable operator, the Hamiltonian of the system. We discuss a rather general situation, and analyse the resulting dynamics if the Hamiltonian is a simple Hermitian matrix.

Statistics and ProbabilityPhysics - Physics and SocietyQuantum PhysicsCompatible and incompatible questionComputer scienceQuantum dynamicsQuantum dynamicTime evolutionHilbert spaceFOS: Physical sciencesBinary numberProbability and statisticsPhysics and Society (physics.soc-ph)Condensed Matter PhysicsHermitian matrixAlgebrasymbols.namesakeOperator (computer programming)symbolsQuantum Physics (quant-ph)Hamiltonian (quantum mechanics)Decision makingSettore MAT/07 - Fisica Matematica
researchProduct

Estimating Mean Lifetime from Partially Observed Events in Nuclear Physics

2022

Abstract The mean lifetime is an important characteristic of particles to be identified in nuclear physics. State-of-the-art particle detectors can identify the arrivals of single radioactive nuclei as well as their subsequent radioactive decays (departures). Challenges arise when the arrivals and departures are unmatched and the departures are only partially observed. An inefficient solution is to run experiments where the arrival rate is set very low to allow for the matching of arrivals and departures. We propose an estimation method that works for a wide range of arrival rates. The method combines an initial estimator and a numerical bias correction technique. Simulations and examples b…

Statistics and ProbabilityPhysicsNuclear physicsdesign of experimentsmissing datanoisy binary searchradioactive decayPoisson processStatistics Probability and Uncertaintyydinfysiikkatilastolliset mallitestimointiradioaktiivisuusJournal of the Royal Statistical Society Series C: Applied Statistics
researchProduct

Duality and spatial inhomogeneity

2001

Within the framework on non-extensive thermostatistics we revisit the recently advanced q-duality concept. We focus our attention here on a modified q-entropic measure of the spatial inhomogeneity for binary patterns. At a fixed length-scale this measure exhibits a generalised duality that links appropriate pairs of q and q' values. The simplest q q' invariant function, without any free parameters, is deduced here. Within an adequate interval q < qo < q', in which the function reaches its maximum value at qo, this invariant function accurately approximates the investigated q-measure, nitidly evidencing the duality phenomenon. In the close vicinity of qo, the approximate meaningful rel…

Statistics and ProbabilityPhysicsStatistical Mechanics (cond-mat.stat-mech)Value (computer science)Binary numberDuality (optimization)FOS: Physical sciencesFunction (mathematics)Interval (mathematics)Condensed Matter PhysicsMeasure (mathematics)Focus (optics)Condensed Matter - Statistical MechanicsMathematical physicsFree parameter
researchProduct

MODERATE DEVIATION PRINCIPLES FOR BIFURCATING MARKOV CHAINS: CASE OF FUNCTIONS DEPENDENT OF ONE VARIABLE

2021

The main purpose of this article is to establish moderate deviation principles for additive functionals of bifurcating Markov chains. Bifurcating Markov chains are a class of processes which are indexed by a regular binary tree. They can be seen as the models which represent the evolution of a trait along a population where each individual has two offsprings. Unlike the previous results of Bitseki, Djellout \& Guillin (2014), we consider here the case of functions which depend only on one variable. So, mainly inspired by the recent works of Bitseki \& Delmas (2020) about the central limit theorem for general additive functionals of bifurcating Markov chains, we give here a moderate deviatio…

Statistics and Probability[MATH.MATH-PR]Mathematics [math]/Probability [math.PR][MATH.MATH-PR] Mathematics [math]/Probability [math.PR]60J80Bifurcating Markov chainsbinary trees[MATH]Mathematics [math]binary trees Mathematics Subject Classification (2020): 60F10deviation inequalitiesMathematics - Probabilitymoderate deviation principles
researchProduct

Monte Carlo simulation of polymers at interfaces

1993

Abstract Polymers at interfaces pose challenging problems to statistical physics because their configurations often differ greatly from the bulk. Computer simulation of coarse-grained models then gives valuable insight and allows stringent tests of various theoretical predictions. Three examples are briefly treated: chain configurations of B-chains in the surface-enriched B-rich layer of an (AB) binary polymer mixture; “frustrated” lamellar ordering in ultra-thin block-copolymer films; and the collapse of polymer brushes in bad solvents.

Statistics and Probabilitychemistry.chemical_classificationMaterials scienceWall effectMonte Carlo methodBinary numberPolymerCondensed Matter PhysicsMolten statechemistryRadius of gyrationLamellar structurePolymer blendStatistical physicsPhysica A: Statistical Mechanics and its Applications
researchProduct

Morphological Analysis of Binary Scene in APR Integrated Environment

2009

This paper describes principles of binary scene [1] morphological analysis in script based application - APR (Analysis, Processing and Recognition). The aim of the method is to find object on the scene and then to describe theirs basic features like edges, neighbors and surface [2]. The algorithm construction gives benefits in terms speed as well as to computation costs, at the same time being capable of presenting number of attributes values for scene and each of the objects. There are also some practical algorithm applications showed.

Surface (mathematics)Computer sciencebusiness.industryComputationMorphological analysisComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPractical algorithmBinary numberComputer visionArtificial intelligenceObject (computer science)business
researchProduct