Search results for "62G10"

showing 3 items of 3 documents

Automatic regrouping of strata in the goodness-of-fit chi-square test

2019

Pearson’s chi-square test is widely employed in social and health sciences to analyze categorical data and contingency tables. For the test to be valid, the sample size must be large enough to provide a minimum number of expected elements per category. This paper develops functions for regrouping strata automatically no matter where they are located, thus enabling the goodness-of-fit test to be performed within an iterative procedure. The functions are written in Excel VBA (Visual Basic for Applications) and in Mathematica. The usefulness and performance of these functions is illustrated by means of a simulation study and the application to different datasets. Finally, the iterative use of …

Contingency tableComputer scienceContinuous Sample of Working Lives62G10 62P25MathematicaSample (statistics):62 Statistics::62P Applications [Classificació AMS]Visual Basic for ApplicationsEconomiaTest (assessment):62 Statistics::62G Nonparametric inference [Classificació AMS]Goodness of fitFinancesSample size determination:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]StatisticsVisual Basic for ApplicationsChi-square testGoodness-of-fit chi-square test statistical software Visual Basic for Applications Mathematica Continuous Sample of Working Livesstatistical softwareGoodness-of-fit chi-square testEconometríaCategorical variable
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General framework for testing Poisson-Voronoi assumption for real microstructures

2020

Modeling microstructures is an interesting problem not just in Materials Science but also in Mathematics and Statistics. The most basic model for steel microstructure is the Poisson-Voronoi diagram. It has mathematically attractive properties and it has been used in the approximation of single phase steel microstructures. The aim of this paper is to develop methods that can be used to test whether a real steel microstructure can be approximated by such a model. Therefore, a general framework for testing the Poisson-Voronoi assumption based on images of 2D sections of real metals is set out. Following two different approaches, according to the use or not of periodic boundary conditions, thre…

FOS: Computer and information sciencesreal microstructuresPoisson-Voronoi diagrams0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchPoisson distribution01 natural sciencesStatistics - ApplicationsMethodology (stat.ME)Set (abstract data type)010104 statistics & probabilitysymbols.namesakehypothesis testingPeriodic boundary conditionsApplied mathematicsApplications (stat.AP)0101 mathematicsStatistics - MethodologyStatistical hypothesis testing021103 operations researchCumulative distribution functionDiagramscalingGeneral Business Management and Accounting62P30 62-00 62-01 62G10persistence landscapeModeling and SimulationsymbolsTopological data analysiscumulative distribution functionVoronoi diagramApplied Stochastic Models in Business and Industry
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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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