Search results for "ASYM"

showing 10 items of 2151 documents

Affine-invariant rank tests for multivariate independence in independent component models

2016

We consider the problem of testing for multivariate independence in independent component (IC) models. Under a symmetry assumption, we develop parametric and nonparametric (signed-rank) tests. Unlike in independent component analysis (ICA), we allow for the singular cases involving more than one Gaussian independent component. The proposed rank tests are based on componentwise signed ranks, à la Puri and Sen. Unlike the Puri and Sen tests, however, our tests (i) are affine-invariant and (ii) are, for adequately chosen scores, locally and asymptotically optimal (in the Le Cam sense) at prespecified densities. Asymptotic local powers and asymptotic relative efficiencies with respect to Wilks’…

Statistics and ProbabilityMultivariate statisticssingular information matricesRank (linear algebra)Gaussianuniform local asymptotic02 engineering and technology01 natural sciencesdistribution-free testsCombinatoricstests for multivariate independence010104 statistics & probabilitysymbols.namesakenormaalius0202 electrical engineering electronic engineering information engineeringApplied mathematics0101 mathematicsStatistique mathématiqueIndependence (probability theory)Parametric statisticsMathematicsDistribution-free testsuniform local asymptotic normalityNonparametric statistics020206 networking & telecommunicationsIndependent component analysisrank testsAsymptotically optimal algorithmsymbolsindependent component models62H1562G35Statistics Probability and UncertaintyUniform local asymptotic normality62G10
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Asymptotics for pooled marginal slicing estimator based on SIRα approach

2005

Pooled marginal slicing (PMS) is a semiparametric method, based on sliced inverse regression (SIR) approach, for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we consider the SIR"@a version (combining the SIR-I and SIR-II approaches) of the PMS estimator and we establish the asymptotic distribution of the estimated matrix of interest. Then the asymptotic normality of the eigenprojector on the estimated effective dimension reduction (e.d.r.) space is derived as well as the asymptotic distributions of each estimated e.d.r. direction and its corresponding eigenvalue.

Statistics and ProbabilityNumerical AnalysisDimensionality reductionStatisticsSliced inverse regressionAsymptotic distributionEstimatorRegression analysisStatistics Probability and UncertaintyMarginal distributionEffective dimensionEigenvalues and eigenvectorsMathematicsJournal of Multivariate Analysis
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Deflation-based separation of uncorrelated stationary time series

2014

In this paper we assume that the observed pp time series are linear combinations of pp latent uncorrelated weakly stationary time series. The problem is then to find an estimate for an unmixing matrix that transforms the observed time series back to uncorrelated time series. The so called SOBI (Second Order Blind Identification) estimate aims at a joint diagonalization of the covariance matrix and several autocovariance matrices with varying lags. In this paper, we propose a novel procedure that extracts the latent time series one by one. The limiting distribution of this deflation-based SOBI is found under general conditions, and we show how the results can be used for the comparison of es…

Statistics and ProbabilityNumerical Analysista112Series (mathematics)matematiikkaCovariance matrixaikasarjatmathematicsta111Asymptotic distributionDeflationBlind signal separationAutocovarianceMatrix (mathematics)StatisticsApplied mathematicsStatistics Probability and Uncertaintytime seriesLinear combinationMathematicsJournal of Multivariate Analysis
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Non-parametric Estimation of the Death Rate in Branching Diffusions

2002

We consider finite systems of diffusing particles in R with branching and immigration. Branching of particles occurs at position dependent rate. Under ergodicity assumptions, we estimate the position-dependent branching rate based on the observation of the particle process over a time interval [0, t]. Asymptotics are taken as t → ∞. We introduce a kernel-type procedure and discuss its asymptotic properties with the help of the local time for the particle configuration. We compute the minimax rate of convergence in squared-error loss over a range of Holder classes and show that our estimator is asymptotically optimal.

Statistics and ProbabilityParticle systemAsymptotically optimal algorithmRate of convergenceErgodicityCalculusEstimatorApplied mathematicsStatistics Probability and UncertaintyMinimaxPoint processMathematicsBranching processScandinavian Journal of Statistics
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Separation of Uncorrelated Stationary time series using Autocovariance Matrices

2015

Blind source separation (BSS) is a signal processing tool, which is widely used in various fields. Examples include biomedical signal separation, brain imaging and economic time series applications. In BSS, one assumes that the observed $p$ time series are linear combinations of $p$ latent uncorrelated weakly stationary time series. The aim is then to find an estimate for an unmixing matrix, which transforms the observed time series back to uncorrelated latent time series. In SOBI (Second Order Blind Identification) joint diagonalization of the covariance matrix and autocovariance matrices with several lags is used to estimate the unmixing matrix. The rows of an unmixing matrix can be deriv…

Statistics and ProbabilitySignal processingSeries (mathematics)Covariance matrixApplied MathematicsAsymptotic distribution020206 networking & telecommunications02 engineering and technology01 natural sciencesBlind signal separation010104 statistics & probabilityMatrix (mathematics)Autocovariance0202 electrical engineering electronic engineering information engineeringApplied mathematics0101 mathematicsStatistics Probability and UncertaintyLinear combinationMathematicsJournal of Time Series Analysis
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Monte Carlo simulations of a trader-based market model

2002

Abstract We present a detailed analysis of the stationary state and the parameter sensitivity of a trader-based market model suggested in Bak et al. (Physica A 246 (1997) 430). The model in question takes only so-called noise-traders into account and its properties are determined by mutual imitation of the traders and volatility feedback. We show that the stationary state of the model can be characterized by a log-normal distribution of the bid and ask prices relative to the current market price. In the stationary state the model is able to reproduce the so-called stylized facts of real markets. This property is stable under variation of the essential parameters of the model, number of trad…

Statistics and ProbabilityStylized factEconophysicsmedia_common.quotation_subjectMonte Carlo methodCondensed Matter PhysicsAsymmetryMarket priceEconomicsEconometricsVolatility (finance)Bid priceStationary statemedia_commonPhysica A: Statistical Mechanics and its Applications
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Portfolio optimisation with strictly positive transaction costs and impulse control

1998

One crucial assumption in modern portfolio theory of continuous-time models is the no transaction cost assumption. This assumption normally leads to trading strategies with infinite variation. However, following such a strategy in the presence of transaction costs will lead to immediate ruin. We present an impulse control approach where the investor can change his portfolio only finitely often in finite time intervals. Further, we consider transaction costs including a fixed and a proportional cost component. For the solution of the resulting control problems we present a formal optimal stopping approach and an approach using quasi-variational inequalities. As an application we derive a non…

Statistics and ProbabilityTransaction costMathematical optimizationExponential utilityMerton's portfolio problemReplicating portfolioEconomicsPortfolio optimisation transaction costs impulse control asymptotic analysis.PortfolioOptimal stoppingStatistics Probability and UncertaintyPortfolio optimizationFinanceModern portfolio theory
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A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS

2019

We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Phase transitionrandom environmentGeneral Mathematicsmedia_common.quotation_subjectmoderate deviationslimit-theoremsmarkov-chainsStatistics::Other StatisticsBranching processdeviation inequalities92D2501 natural sciencesAsymmetry010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Convergence (routing)[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Applied mathematics60C05[MATH]Mathematics [math]0101 mathematicsautoregressive process60J20lawMathematicsBranching processmedia_commonEvent (probability theory)parametersconvergenceMarkov chain010102 general mathematics[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO][MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Large deviationslarge deviations Mathematics Subject Classification (2010): 60J8060K37Autoregressive modelcellsLarge deviations theoryStatistics Probability and Uncertaintyasymmetry60F10
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Test of the Latent Dimension of a Spatial Blind Source Separation Model

2024

We assume a spatial blind source separation model in which the observed multivariate spatial data is a linear mixture of latent spatially uncorrelated random fields containing a number of pure white noise components. We propose a test on the number of white noise components and obtain the asymptotic distribution of its statistic for a general domain. We also demonstrate how computations can be facilitated in the case of gridded observation locations. Based on this test, we obtain a consistent estimator of the true dimension. Simulation studies and an environmental application in the Supplemental Material demonstrate that our test is at least comparable to and often outperforms bootstrap-bas…

Statistics and Probabilitymonimuuttujamenetelmätsignaalinkäsittelykernel functionFOS: Mathematicsspatial bootstrapMathematics - Statistics Theorymultivariate spatial dataStatistics Theory (math.ST)paikkatietoanalyysiStatistics Probability and Uncertaintyasymptotic distributionsignal number
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Lévy processes in bounded domains: path-wise reflection scenarios and signatures of confinement

2022

We discuss an impact of various (path-wise) reflection-from-the barrier scenarios upon confining properties of a paradigmatic family of symmetric $\alpha $-stable L\'{e}vy processes, whose permanent residence in a finite interval on a line is secured by a two-sided reflection. Depending on the specific reflection "mechanism", the inferred jump-type processes differ in their spectral and statistical characteristics, like e.g. relaxation properties, and functional shapes of invariant (equilibrium, or asymptotic near-equilibrium) probability density functions in the interval. The analysis is carried out in conjunction with attempts to give meaning to the notion of a reflecting L\'{e}vy process…

Statistics and Probabilityreflection scenariosasymptotic pdfs in the intervalpath-wise analysisreflecting boundary dataStatistical Mechanics (cond-mat.stat-mech)Probability (math.PR)General Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsMathematical Physics (math-ph)reflecting L´evy processMathematics - Analysis of PDEsModeling and SimulationFOS: Mathematicsfractional LaplacianCondensed Matter - Statistical MechanicsMathematics - ProbabilityMathematical Physicsrandom walk approximationAnalysis of PDEs (math.AP)Journal of Physics A-Mathematical and Theoretical
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