Search results for " Statistical"

showing 10 items of 1649 documents

PRINCIPAL POLYNOMIAL ANALYSIS

2014

© 2014 World Scientific Publishing Company. This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves instead of straight lines. Contrarily to previous approaches PPA reduces to performing simple univariate regressions which makes it computationally feasible and robust. Moreover PPA shows a number of interesting analytical properties. First PPA is a volume preserving map which in turn guarantees the existence of the inverse. Second such an inverse can be obtained…

FOS: Computer and information sciencesPolynomialComputer Networks and CommunicationsComputer scienceMachine Learning (stat.ML)02 engineering and technologyReduction (complexity)03 medical and health sciencessymbols.namesake0302 clinical medicineStatistics - Machine LearningArtificial Intelligence0202 electrical engineering electronic engineering information engineeringPrincipal Polynomial AnalysisPrincipal Component AnalysisMahalanobis distanceModels StatisticalCodingDimensionality reductionNonlinear dimensionality reductionGeneral MedicineClassificationDimensionality reductionManifold learningNonlinear DynamicsMetric (mathematics)Jacobian matrix and determinantsymbolsRegression Analysis020201 artificial intelligence & image processingNeural Networks ComputerAlgorithmAlgorithms030217 neurology & neurosurgeryCurse of dimensionalityInternational Journal of Neural Systems
researchProduct

Simulation-based marginal likelihood for cluster strong lensing cosmology

2015

Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with $\Lambda$CDM cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, $\alpha$ and $\beta$. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected …

FOS: Computer and information sciencesSTATISTICAL [METHODS]Cold dark matterCosmology and Nongalactic Astrophysics (astro-ph.CO)NUMERICAL [METHODS]Ciencias FísicasPosterior probabilityFOS: Physical sciencesAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesStatistics - ApplicationsCosmologymethods: numerical//purl.org/becyt/ford/1 [https]cosmology: theory0103 physical sciencesCluster (physics)Applications (stat.AP)Statistical physics010303 astronomy & astrophysicsInstrumentation and Methods for Astrophysics (astro-ph.IM)Galaxy clusterPhysicsmethods: statisticalgravitational lensing: strong; methods: numerical; methods: statistical; galaxies: clusters: general; cosmology: theory010308 nuclear & particles physicsgravitational lensing: strongAstronomy and AstrophysicsBayes factor//purl.org/becyt/ford/1.3 [https]STRONG [GRAVITATIONAL LENSING]RedshiftMarginal likelihoodAstronomíaTHEORY [COSMOLOGY]Space and Planetary Sciencegalaxies: clusters: generalPhysics - Data Analysis Statistics and ProbabilityCLUSTERS: GENERAL [GALAXIES]Astrophysics - Instrumentation and Methods for AstrophysicsData Analysis Statistics and Probability (physics.data-an)CIENCIAS NATURALES Y EXACTASAstrophysics - Cosmology and Nongalactic Astrophysics
researchProduct

Microstructure reconstruction using entropic descriptors

2009

A multi-scale approach to the inverse reconstruction of a pattern's microstructure is reported. Instead of a correlation function, a pair of entropic descriptors (EDs) is proposed for stochastic optimization method. The first of them measures a spatial inhomogeneity, for a binary pattern, or compositional one, for a greyscale image. The second one quantifies a spatial or compositional statistical complexity. The EDs reveal structural information that is dissimilar, at least in part, to that given by correlation functions at almost all of discrete length scales. The method is tested on a few digitized binary and greyscale images. In each of the cases, the persuasive reconstruction of the mic…

FOS: Computer and information sciencesStatistical Mechanics (cond-mat.stat-mech)General MathematicsComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionGeneral EngineeringGeneral Physics and AstronomyBinary numberInverseFOS: Physical sciencesBinary patternGrayscaleImage (mathematics)CorrelationCorrelation function (statistical mechanics)Computer Science::Computer Vision and Pattern RecognitionStochastic optimizationStatistical physicsCondensed Matter - Statistical MechanicsMathematics
researchProduct

A novel exact representation of stationary colored Gaussian processes (fractional differential approach)

2010

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equations whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

FOS: Computer and information sciencesStatistics and ProbabilityDifferential equationFOS: Physical sciencesGeneral Physics and AstronomyStatistics - ComputationStochastic differential equationsymbols.namesakeSpectral MomentsApplied mathematicsStationary processeGaussian processCondensed Matter - Statistical MechanicsComputation (stat.CO)Mathematical PhysicsMathematicsGeneralized functionStatistical Mechanics (cond-mat.stat-mech)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)White noiseClosed and exact differential formsColors of noiseGaussian noiseFractional CalculuModeling and SimulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
researchProduct

Community characterization of heterogeneous complex systems

2011

We introduce an analytical statistical method to characterize the communities detected in heterogeneous complex systems. By posing a suitable null hypothesis, our method makes use of the hypergeometric distribution to assess the probability that a given property is over-expressed in the elements of a community with respect to all the elements of the investigated set. We apply our method to two specific complex networks, namely a network of world movies and a network of physics preprints. The characterization of the elements and of the communities is done in terms of languages and countries for the movie network and of journals and subject categories for papers. We find that our method is ab…

FOS: Computer and information sciencesStatistics and Probabilityrandom graphs networks statistical inference socio-economic networksPhysics - Physics and SocietyTheoretical computer scienceProperty (programming)Complex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)socio-economic networksStatistical inferenceSocial and Information Networks (cs.SI)Random graphComputer Science - Social and Information NetworksStatistical and Nonlinear PhysicsProbability and statisticsComplex networkSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Hypergeometric distributionPhysics - Data Analysis Statistics and ProbabilitynetworkStatistics Probability and UncertaintyNull hypothesisData Analysis Statistics and Probability (physics.data-an)random graphstatistical inferenceJournal of Statistical Mechanics: Theory and Experiment
researchProduct

Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI

2015

Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…

FOS: Computer and information sciencesgranger causality (GC)Multivariate statisticsComputer scienceRestComputer Science - Information TheoryBiomedical EngineeringsynergyFOS: Physical sciencescomputer.software_genre01 natural sciences03 medical and health sciences0302 clinical medicineGranger causality0103 physical sciencesConnectomeRedundancy (engineering)HumansBrain connectivityTime series010306 general physicsModels StatisticalHuman Connectome ProjectResting state fMRIredundancybusiness.industryInformation Theory (cs.IT)functional magnetic resonance imaging (fMRI)BrainPattern recognitionComplex networkMagnetic Resonance ImagingVariable (computer science)Physics - Data Analysis Statistics and ProbabilityQuantitative Biology - Neurons and CognitionFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPairwise comparisonNeurons and Cognition (q-bio.NC)Artificial intelligenceData miningNerve Netbusinesscomputer030217 neurology & neurosurgeryData Analysis Statistics and Probability (physics.data-an)
researchProduct

Sector identification in a set of stock return time series traded at the London Stock Exchange

2005

We compare some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a portfolio of stocks traded at the London Stock Exchange. The investigated time series are recorded both at a daily time horizon and at a 5-minute time horizon. The correlation coefficient matrix is very different at different time horizons confirming that more structured correlation coefficient matrices are observed for long time horizons. All the considered methods are able to detect econo…

FOS: Economics and businessPhysics - Physics and SocietyStatistical Finance (q-fin.ST)SYSTEMSEXPRESSION DATAQuantitative Finance - Statistical FinanceFOS: Physical sciencesFINANCIAL-MARKETSDisordered Systems and Neural Networks (cond-mat.dis-nn)Physics and Society (physics.soc-ph)Condensed Matter - Disordered Systems and Neural NetworksMATRICESNOISE
researchProduct

Tick size and price diffusion

2010

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties…

FOS: Economics and businessStatistical Finance (q-fin.ST)Market microstructureEconophysicsFinancial markets Market microstructure Stochastic processes EconophysicsQuantitative Finance - Statistical FinanceFinancial marketStochastic processe
researchProduct

On the origin of power law tails in price fluctuations

2003

In a recent Nature paper, Gabaix et al. \cite{Gabaix03} presented a theory to explain the power law tail of price fluctuations. The main points of their theory are that volume fluctuations, which have a power law tail with exponent roughly -1.5, are modulated by the average market impact function, which describes the response of prices to transactions. They argue that the average market impact function follows a square root law, which gives power law tails for prices with exponent roughly -3. We demonstrate that the long-memory nature of order flow invalidates their statistical analysis of market impact, and present a more careful analysis that properly takes this into account. This makes i…

FOS: Economics and businessStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Financial economicsMathematical financeEconomicsQuantitative Finance - Statistical FinanceFOS: Physical sciencesGeneral Economics Econometrics and FinancePower lawFinance Commerce correlation matrixFinanceCondensed Matter - Statistical Mechanics
researchProduct

Using the Scaling Analysis to Characterize Financial Markets

2003

We empirically analyze the scaling properties of daily Foreign Exchange rates, Stock Market indices and Bond futures across different financial markets. We study the scaling behaviour of the time series by using a generalized Hurst exponent approach. We verify the robustness of this approach and we compare the results with the scaling properties in the frequency-domain. We find evidence of deviations from the pure Brownian motion behavior. We show that these deviations are associated with characteristics of the specific markets and they can be, therefore, used to distinguish the different degrees of development of the markets.

FOS: Economics and businessStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)jel:G1Quantitative Finance - Statistical FinanceFOS: Physical sciencesCondensed Matter - Statistical Mechanicsscaling exponents time series analysis multi-fractals financial market
researchProduct