Search results for "DEPENDENCE"

showing 10 items of 2462 documents

Independent component analysis based on symmetrised scatter matrices

2007

A new method for separating the mixtures of independent sources has been proposed recently in [Oja et al. (2006). Scatter matrices and independent component analysis. Austrian J. Statist., to appear]. This method is based on two scatter matrices with the so-called independence property. The corresponding method is now further examined. Simple simulation studies are used to compare the performance of so-called symmetrised scatter matrices in solving the independence component analysis problem. The results are also compared with the classical FastICA method. Finally, the theory is illustrated by some examples. peerReviewed

Statistics and ProbabilityApplied MathematicsIndependence propertyStatistical computationhajontamatriisitIndependent component analysisComputational MathematicsComputational Theory and MathematicsComponent analysisSimple (abstract algebra)CalculusSource separationFastICAApplied mathematicsICAIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
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Sparse Sampling and Maximum Likelihood Estimation for Boolean Models

1991

A condition for practical independence of contact distribution functions in Boolean models is obtained. This result allows the authors to use maximum likelihcod methods, via sparse sampling, for estimating unknown parameters of an isotropic Boolean model. The second part of this paper is devoted to a simulation study of the proposed method. AMS classification: 60D05

Statistics and ProbabilityBiometricsBoolean modelIsotropySampling (statistics)General MedicineLikelihood-ratio testStatisticsMaximum satisfiability problemStatistics Probability and UncertaintyAlgorithmIndependence (probability theory)Standard Boolean modelMathematicsBiometrical Journal
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Response models for mixed binary and quantitative variables

1992

SUMMARY A number of special representations are considered for the joint distribution of qualitative, mostly binary, and quantitative variables. In addition to the conditional Gaussian models and to conditional Gaussian regression chain models some emphasis is placed on models derived from an underlying multivariate normal distribution and on models in which discrete probabilities are specified linearly in terms of unknown parameters. The possibilities for choosing between the models empirically are examined, as well as the testing of independence and conditional independence and the estimation of parameters. Often the testing of independence is exactly or nearly the same for a number of di…

Statistics and ProbabilityChain rule (probability)Applied MathematicsGeneral MathematicsMultivariate normal distributionConditional probability distributionAgricultural and Biological Sciences (miscellaneous)Discriminative modelConditional independenceJoint probability distributionStatisticsStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesConditional varianceIndependence (probability theory)MathematicsBiometrika
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On Association Models Defined over Independence Graphs

1998

Conditions on joint distributions are given under which two variables will be conditionally associated whenever an independence graph does not imply a corresponding conditional independence statement. To this end the notions of parametric cancellation, of stable paths and of quasi-linear models are discussed in some detail.

Statistics and ProbabilityCombinatoricsStatement (computer science)Discrete mathematicsConditional independenceJoint probability distributionIndependence (mathematical logic)Matrix decompositionParametric statisticsCholesky decompositionMathematicsCorresponding conditionalBernoulli
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Modeling accident risk at the road level through zero-inflated negative binomial models: A case study of multiple road networks

2021

Abstract This paper presents a case study carried out in multiple cities of the Valencian Community (Spain) to determine the effect of sociodemographic and road characteristics on traffic accident risk. The analyzes are performed at the road segment level, considering the linear network representing the road structure of each city as a spatial lattice. The number of accidents observed in each road segment from 2010 to 2019 is taken as the response variable, and a zero-inflated modeling approach is considered. Count overdispersion and spatial dependence are also accounted for. Despite the complexity and sparsity of the data, the fitted models performed considerably well, with few exceptions.…

Statistics and ProbabilityComputer sciencespatial dependence0208 environmental biotechnologyAccident riskMagnitude (mathematics)Distribution (economics)02 engineering and technologyManagement Monitoring Policy and Law01 natural sciencestraffic accidents010104 statistics & probabilityOverdispersionCovariateStatisticsZero-inflated model0101 mathematicsComputers in Earth SciencesSpatial dependencelattice structurebusiness.industryIntegrated Nested Laplace Approximationzero-inflated model020801 environmental engineeringVariable (computer science)linear networksbusiness
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Test Procedures in Configural Frequency Analysis (CFA) Controlling the Local and Multiple Level

1987

The test statistics used until now in the CFA have been developed under the assumption of the overall hypothesis of total independence. Therefore, the multiple test procedures based on these statistics are really only different tests of the overall hypothesis. If one likes to test a special cell hypothesis, one should only assume that this hypothesis is true and not the whole overall hypothesis. Such cell tests can then be used as elements of a multiple test procedure. In this paper it is shown that the usual test procedures can be very anticonservative (except of the two-dimensional, and, for some procedures, the three-dimensional case), and corrected test procedures are developed. Further…

Statistics and ProbabilityContingency tableGeneral MedicineTest (assessment)StatisticsPortmanteau testEconometricsChi-square testTest statisticStatistics Probability and UncertaintyConfigural frequency analysisIndependence (probability theory)MathematicsStatistical hypothesis testingBiometrical Journal
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Binary distributions of concentric rings

2014

We introduce families of jointly symmetric, binary distributions that are generated over directed star graphs whose nodes represent variables and whose edges indicate positive dependences. The families are parametrized in terms of a single parameter. It is an outstanding feature of these distributions that joint probabilities relate to evenly spaced concentric rings. Kronecker product characterizations make them computationally attractive for a large number of variables. We study the behavior of different measures of dependence and derive maximum likelihood estimates when all nodes are observed and when the inner node is hidden.

Statistics and ProbabilityContingency tableKronecker productDiscrete mathematicsNumerical AnalysisBinary numberStar (graph theory)Combinatoricssymbols.namesakeConditional independenceJoint probability distributionsymbolsFeature (machine learning)Node (circuits)Statistics Probability and UncertaintyMathematicsJournal of Multivariate Analysis
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Spatio-temporal modelling of COVID-19 incident cases using Richards’ curve: An application to the Italian regions

2021

Abstract We introduce an extended generalised logistic growth model for discrete outcomes, in which spatial and temporal dependence are dealt with the specification of a network structure within an Auto-Regressive approach. A major challenge concerns the specification of the network structure, crucial to consistently estimate the canonical parameters of the generalised logistic curve, e.g. peak time and height. We compared a network based on geographic proximity and one built on historical data of transport exchanges between regions. Parameters are estimated under the Bayesian framework, using Stan probabilistic programming language. The proposed approach is motivated by the analysis of bot…

Statistics and ProbabilityCoronavirus disease 2019 (COVID-19)Computer scienceNetwork structureGeographic proximityCOVID-19COVID-19; conditional auto-regressive; Stan; generalised logistic growthManagement Monitoring Policy and LawConditional Auto-RegressiveCOVID-19 Conditional Auto-Regressive Stan generalised logistic growthStanEconometricsIndependence (mathematical logic)Bayesian frameworkComputers in Earth SciencesLogistic functionProbabilistic programming languageSettore SECS-S/01 - StatisticaSettore SECS-S/01generalised logistic growth
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A generalization of the Binomial distribution based on the dependence ratio

2015

We propose a generalization of the Binomial distribution, called DR-Binomial, which accommodates dependence among units through a model based on the dependence ratio (Ekholm et al., Biometrika, 82, 1995, 847). Properties of the DR-Binomial are discussed, and the constraints on its parameter space are studied in detail. Likelihood-based inference is presented, using both the joint and profile likelihoods; the usefulness of the DR-Binomial in applications is illustrated on a real dataset displaying negative unit-dependence, and hence under-dispersion compared with the Binomial. Although the DR-Binomial turns out to be a reparameterization of Altham's Additive-Binomial and Kupper-Haseman's Cor…

Statistics and ProbabilityDependent binary dataGeneralized Binomial distributionSettore SECS-S/01 - StatisticaDependence ratio
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Sign test of independence between two random vectors

2003

A new affine invariant extension of the quadrant test statistic Blomqvist (Ann. Math. Statist. 21 (1950) 593) based on spatial signs is proposed for testing the hypothesis of independence. In the elliptic case, the new test statistic is asymptotically equivalent to the interdirection test by Gieser and Randles (J. Amer. Statist. Assoc. 92 (1997) 561) but is easier to compute in practice. Limiting Pitman efficiencies and simulations are used to compare the test to the classical Wilks’ test. peerReviewed

Statistics and ProbabilityDiscrete mathematicsStatistics::TheoryMultivariate random variableExtension (predicate logic)robustnessQuadrant testPitman efficiencyTest (assessment)Exact testStatisticsChi-square testTest statisticSign testaffine invarianceStatistics Probability and UncertaintyIndependence (probability theory)MathematicsWilks’ test
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