Search results for "TRANSFORMATION"

showing 10 items of 1634 documents

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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The asymptotic covariance matrix of the Oja median

2003

The Oja median, based on a sample of multivariate data, is an affine equivariant estimate of the centre of the distribution. It reduces to the sample median in one dimension and has several nice robustness and efficiency properties. We develop different representations of its asymptotic variance and discuss ways to estimate this quantity. We consider symmetric multivariate models and also the more narrow elliptical models. A small simulation study is included to compare finite sample results to the asymptotic formulas.

Statistics and ProbabilityCombinatoricsDelta methodMultivariate statisticsMatrix (mathematics)Multivariate analysis of varianceDimension (vector space)Matrix t-distributionApplied mathematicsEquivariant mapAffine transformationStatistics Probability and UncertaintyMathematicsStatistics & Probability Letters
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A Unified Approach to Likelihood Inference on Stochastic Orderings in a Nonparametric Context

1998

Abstract For data in a two-way contingency table with ordered margins, we consider various hypotheses of stochastic orders among the conditional distributions considered by rows and show that each is equivalent to requiring that an invertible transformation of the vectors of conditional row probabilities satisfies an appropriate set of linear inequalities. This leads to the construction of a general algorithm for maximum likelihood estimation under multinomial sampling and provides a simple framework for deriving the asymptotic distribution of log-likelihood ratio tests. The usual stochastic ordering and the so called uniform and likelihood ratio orderings are considered as special cases. I…

Statistics and ProbabilityCombinatoricsIndependent and identically distributed random variablesLinear inequalityTransformation (function)Likelihood-ratio testAsymptotic distributionApplied mathematicsConditional probability distributionStatistics Probability and UncertaintyStochastic orderingStatistical hypothesis testingMathematicsJournal of the American Statistical Association
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Inference based on the affine invariant multivariate Mann–Whitney–Wilcoxon statistic

2003

A new affine invariant multivariate analogue of the two-sample Mann–Whitney–Wilcoxon test based on the Oja criterion function is introduced. The associated affine equivariant estimate of shift, the multivariate Hodges-Lehmann estimate, is also considered. Asymptotic theory is developed to provide approximations for null distribution as well as for a sequence of contiguous alternatives to consider limiting efficiencies of the test and estimate. The theory is illustrated by an example. Hettmansperger et al. [9] considered alternative slightly different affine invariant extensions also based on the Oja criterion. The methods proposed in this paper are computationally more intensive, but surpri…

Statistics and ProbabilityDiscrete mathematicsMultivariate statisticsWilcoxon signed-rank testNull distributionMatrix t-distributionApplied mathematicsMultivariate normal distributionAffine transformationStatistics Probability and UncertaintyMathematicsNormal-Wishart distributionMultivariate stable distributionJournal of Nonparametric Statistics
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A consistent modification of a test for independence based on the empirical characteristic function

1998

A modification of a test for independence based on the empirical characteristic function is investigated. The initial test is not consistent in the general case. The modification makes the test always consistent and asymptotically distribution free. It is based on a special transformation of the data.

Statistics and ProbabilityDistribution freeTransformation (function)Characteristic function (probability theory)Applied MathematicsGeneral MathematicsMathematical analysisApplied mathematicsEmpirical characteristic functionIndependence (probability theory)MathematicsTest (assessment)Journal of Mathematical Sciences
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Holt–Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data

2007

Abstract This paper provides a formulation for the additive Holt–Winters forecasting procedure that simplifies both obtaining maximum likelihood estimates of all unknowns, smoothing parameters and initial conditions, and the computation of point forecasts and reliable predictive intervals. The stochastic component of the model is introduced by means of additive, uncorrelated, homoscedastic and Normal errors, and then the joint distribution of the data vector, a multivariate Normal distribution, is obtained. In the case where a data transformation was used to improve the fit of the model, cumulative forecasts are obtained here using a Monte-Carlo approximation. This paper describes the metho…

Statistics and ProbabilityExponential smoothingData transformation (statistics)Prediction intervalMultivariate normal distributionJoint probability distributionHomoscedasticityStatisticsEconometricsStatistics Probability and UncertaintyTime seriesPhysics::Atmospheric and Oceanic PhysicsSmoothingMathematicsJournal of Applied Statistics
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Phase transformation kinetics in d-dimensional grains-containing systems: diffusion-type model

1998

Abstract An analytical approach to the phase transformation in d-dimensional grains-containing complex systems is offered. It is based on considering the mechanism of surface material exchange among neighbouring grains as the so-called state-dependent diffusion process, where the diffusion function is related to the magnitude of the grain boundary. The approach proposed deals with the kinetics of that ensemble under circumstances of a volume increase of the new phase or microstructure. Probabilistic characteristics of the process are derived and analyzed. A comparison with 2D modelling of similar kind is presented for the 3D case, and some possible practical realizations of the situation un…

Statistics and ProbabilityGrain growthMaterials scienceTransformation (function)Diffusion processPhase (matter)Complex systemThermodynamicsGrain boundary diffusion coefficientGrain boundaryDiffusion (business)Condensed Matter PhysicsPhysica A: Statistical Mechanics and its Applications
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Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range

2014

A Bayesian solution is suggested for the modelling of spatial point patterns with inhomogeneous hard-core radius using Gaussian processes in the regularization. The key observation is that a straightforward use of the finite Gibbs hard-core process likelihood together with a log-Gaussian random field prior does not work without penalisation towards high local packing density. Instead, a nearest neighbour Gibbs process likelihood is used. This approach to hard-core inhomogeneity is an alternative to the transformation inhomogeneous hard-core modelling. The computations are based on recent Markovian approximation results for Gaussian fields. As an application, data on the nest locations of Sa…

Statistics and ProbabilityMathematical optimizationGaussianBayesian probabilityBayesian analysisMarkov processRegularization (mathematics)symbols.namesakeGaussian process regularisationPERFECT SIMULATIONRange (statistics)Statistical physicsGaussian processMathematicsta113ta112Random fieldApplied MathematicsInhomogeneousSand Martin's nestsTRANSFORMATIONHard-core point processComputational MathematicsTransformation (function)Computational Theory and MathematicssymbolsINFERENCECOMPUTATIONAL STATISTICS AND DATA ANALYSIS
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Affine Invariant Multivariate Sign and Rank Tests and Corresponding Estimates: a Review

1999

The paper reviews recent contributions to the statistical inference methods, tests and estimates, based on the generalized median of Oja. Multivariate analogues of sign and rank concepts, affine invariant one-sample and two-sample sign tests and rank tests, affine equivariant median and Hodges–Lehmann-type estimates are reviewed and discussed. Some comparisons are made to other generalizations. The theory is illustrated by two examples.

Statistics and ProbabilityMultivariate statisticsPure mathematicsHodges–Lehmann estimatorRank (linear algebra)StatisticsStatistical inferenceEquivariant mapSign testAffine transformationStatistics Probability and UncertaintySign (mathematics)MathematicsScandinavian Journal of Statistics
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Influence functions and efficiencies of the canonical correlation and vector estimates based on scatter and shape matrices

2006

In this paper, the influence functions and limiting distributions of the canonical correlations and coefficients based on affine equivariant scatter matrices are developed for elliptically symmetric distributions. General formulas for limiting variances and covariances of the canonical correlations and canonical vectors based on scatter matrices are obtained. Also the use of the so-called shape matrices in canonical analysis is investigated. The scatter and shape matrices based on the affine equivariant Sign Covariance Matrix as well as the Tyler's shape matrix serve as examples. Their finite sample and limiting efficiencies are compared to those of the Minimum Covariance Determinant estima…

Statistics and ProbabilityNumerical AnalysisSign covariance matrixKanoniset korrelaatiot ja vektoritCovariance matrixMathematical analysisTyler's estimateShape matrixCanonical vectorsCovarianceCanonical correlationsCanonical analysisMatrix (mathematics)Canonical variablesCalculusSymmetric matrixEquivariant mapAffine transformationStatistics Probability and UncertaintyCanonical correlationMathematicsJournal of Multivariate Analysis
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