Search results for "Linear"

showing 10 items of 7165 documents

Wronskian and Casorati determinant representations for Darboux–Pöschl–Teller potentials and their difference extensions

2009

We consider some special reductions of generic Darboux?Crum dressing formulae and of their difference versions. As a matter of fact, we obtain some new formulae for Darboux?P?schl?Teller (DPT) potentials by means of Wronskian determinants. For their difference deformations (called DDPT-I and DDPT-II potentials) and the related eigenfunctions, we obtain new formulae described by the ratios of Casorati determinants given by the functional difference generalization of the Darboux?Crum dressing formula.

Statistics and ProbabilityAlgebraPure mathematicsNonlinear Sciences::Exactly Solvable and Integrable SystemsGeneralizationWronskianModeling and SimulationGeneral Physics and AstronomyStatistical and Nonlinear PhysicsEigenfunctionMathematical PhysicsMathematicsJournal of Physics A: Mathematical and Theoretical
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Moderating effects of subgroups in linear models

1989

SUMMARY Possibilities for moderating effects of a subgrouping variable on strength or direction of an association have been much discussed by social scientists but have not been given satisfactory statistical formulations. The results concern directed measures of associations in linear models containing just three variables. Some key words: Analysis of covariance; Analysis of variance; cG-distribution; Conditional independence; Graphical chain model; Parallel regressions; Yule-Simpson paradox. 1. INTRODUCTION Linear models are commonly used as a framework to estimate and test how a continuous response variable depends on potential influencing variables. This paper is concerned with the situ…

Statistics and ProbabilityAnalysis of covarianceeducation.field_of_studyApplied MathematicsGeneral MathematicsPopulationLinear modelContext (language use)ModerationAgricultural and Biological Sciences (miscellaneous)Conditional independenceStatisticsEconometricsStatistics Probability and UncertaintyGeneral Agricultural and Biological ScienceseducationRandom variableMathematicsVariable (mathematics)Biometrika
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Use of functionals in linearization and composite estimation with application to two-sample survey data

2009

An important problem associated with two-sample surveys is the estimation of nonlinear functions of finite population totals such as ratios, correlation coefficients or measures of income inequality. Computation and estimation of the variance of such complex statistics are made more difficult by the existence of overlapping units. In one-sample surveys, the linearization method based on the influence function approach is a powerful tool for variance estimation. We introduce a two-sample linearization technique that can be viewed as a generalization of the one-sample influence function approach. Our technique is based on expressing the parameters of interest as multivariate functionals of fi…

Statistics and ProbabilityAnalysis of covarianceeducation.field_of_studyOptimal estimationApplied MathematicsGeneral MathematicsPopulationEstimatorVariance (accounting)Agricultural and Biological Sciences (miscellaneous)One-way analysis of varianceDelta methodLinearizationStatisticsApplied mathematicsStatistics Probability and UncertaintyGeneral Agricultural and Biological ScienceseducationB- ECONOMIE ET FINANCEMathematicsBiometrika
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Forecasting time series with missing data using Holt's model

2009

This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.

Statistics and ProbabilityApplied MathematicsAutocorrelationExponential smoothingLinear modelData transformation (statistics)EstimatorMissing dataExpectation–maximization algorithmStatisticsStatistics Probability and UncertaintyAdditive modelAlgorithmMathematicsJournal of Statistical Planning and Inference
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Derived variables calculated from similar joint responses: some characteristics and examples

1995

Abstract A technique (Cox and Wermuth, 1992) is reviewed for finding linear combinations of a set of response variables having special relations of linear conditional independence with a set of explanatory variables. A theorem in linear algebra is used both to examine conditions in which the derived variables take a specially simple form and lead to reduced computations. Examples are discussed of medical and psychological investigations in which the method has aided interpretation.

Statistics and ProbabilityApplied MathematicsDesign matrixComputational MathematicsComputational Theory and MathematicsConditional independenceLinear predictor functionLinear algebraCalculusApplied mathematicsMarginal distributionCanonical correlationLinear combinationIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
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Block Based Deconvolution Algorithm Using Spline Wavelet Packets

2010

This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the…

Statistics and ProbabilityApplied MathematicsSpline waveletCondensed Matter PhysicsDeconvolution · Wavelet packet · Spline · RegularityWavelet packet decompositionSpline (mathematics)Quadratic equationModeling and SimulationOrthonormal basisGeometry and TopologyComputer Vision and Pattern RecognitionDeconvolutionThin plate splineLinear combinationAlgorithmMathematics
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On Independent Component Analysis with Stochastic Volatility Models

2017

Consider a multivariate time series where each component series is assumed to be a linear mixture of latent mutually independent stationary time series. Classical independent component analysis (ICA) tools, such as fastICA, are often used to extract latent series, but they don't utilize any information on temporal dependence. Also financial time series often have periods of low and high volatility. In such settings second order source separation methods, such as SOBI, fail. We review here some classical methods used for time series with stochastic volatility, and suggest modifications of them by proposing a family of vSOBI estimators. These estimators use different nonlinearity functions to…

Statistics and ProbabilityAutoregressive conditional heteroskedasticity01 natural sciencesQA273-280GARCH model010104 statistics & probabilityblind source separation0502 economics and businessSource separationEconometricsApplied mathematics0101 mathematics050205 econometrics MathematicsStochastic volatilitymultivariate time seriesApplied MathematicsStatistics05 social sciencesAutocorrelationEstimatorIndependent component analysisHA1-4737nonlinear autocorrelationFastICAStatistics Probability and UncertaintyVolatility (finance)Probabilities. Mathematical statistics
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Tests against stationary and explosive alternatives in vector autoregressive models

2008

.  The article proposes new tests for the number of unit roots in vector autoregressive models based on the eigenvalues of the companion matrix. Both stationary and explosive alternatives are considered. The limiting distributions of test statistics depend only on the number of unit roots. Size and power are investigated, and it is found that the new test against some stationary alternatives compares favourably with the widely used likelihood ratio test for the cointegrating rank. The powers are prominently higher against explosive than against stationary alternatives. Some empirical examples are provided to show how to use the new tests with real data.

Statistics and ProbabilityAutoregressive modelExplosive materialRank (linear algebra)Applied MathematicsLikelihood-ratio testCompanion matrixEconometricsUnit rootStatistics Probability and UncertaintyEigenvalues and eigenvectorsMathematicsStatistical hypothesis testingJournal of Time Series Analysis
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Is the p-Value a Suitable Basis for the Construction of Measures of Evidence? Comment on “The Role of p-Values in Judging the Strength of Evidence an…

2020

Dr. Gibson has to be congratulated for having enriched the wealth of articles written in response to the ASA statement on p-values of 2016 by a valuable and thoughtful contribution. We particularly...

Statistics and ProbabilityBasis (linear algebra)Statement (logic)Pharmaceutical Science01 natural sciences010104 statistics & probability03 medical and health sciencesStrength of evidence0302 clinical medicineReplication (statistics)030212 general & internal medicinep-value0101 mathematicsPositive economicsPsychologyStatistics in Biopharmaceutical Research
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Isotropic stochastic flow of homeomorphisms on Rd associated with the critical Sobolev exponent

2008

Abstract We consider the critical Sobolev isotropic Brownian flow in R d ( d ≥ 2 ) . On the basis of the work of LeJan and Raimond [Y. LeJan, O. Raimond, Integration of Brownian vector fields, Ann. Probab. 30 (2002) 826–873], we prove that the corresponding flow is a flow of homeomorphisms. As an application, we construct an explicit solution, which is also unique in a certain space, to the stochastic transport equation when the associated Gaussian vector fields are divergence free.

Statistics and ProbabilityBasis (linear algebra)Stochastic processApplied MathematicsMathematical analysisSpace (mathematics)Sobolev spaceStochastic differential equationMathematics::ProbabilityFlow (mathematics)Modeling and SimulationVector fieldBrownian motionMathematicsStochastic Processes and their Applications
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