Search results for "Uncertainty"

showing 10 items of 1010 documents

The geography of Spanish bank branches

2014

This article analyzes the determinants of bank branch location in Spain taking the role of geography explicitly into account. After a long period of intense territorial expansion, especially by savings banks, many of these firms are now involved in merger processes triggered off by the financial crisis, most of which entail the closing of many branches. However, given the contributions of this type of banks to limit financial exclusion, this process might exacerbate the consequences of the crisis for some disadvantaged social groups. Related problems such as new banking regulation initiatives (Basel III), or the current excess capacity in the sector add further relevance to this problem. We…

Statistics and ProbabilityActuarial sciencemunicipalityFinancial economicsProcess (engineering)bankBayesian statisticsbranchR1Basel IIIGeneralized linear mixed modelDisadvantagedSocial groupFinancial crisisRelevance (law)Capacity utilizationG21Statistics Probability and UncertaintyC11Journal of Applied Statistics
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A Comparison of Formulae for Calculating Cost-Efficient Sample Sizes of Case-Control Studies with an Internal Validation Scheme

2000

When a case-control study is planned to include an internal validation study, the sample size of the study and the proportion of validated observations has to be calculated. There are a variety of alternative methods to accomplish this. In this article some possible procedures will be compared in order to clarify whether considerable differences in the suggested optimal designs occur, dependent on the used method.

Statistics and ProbabilityAlternative methodsScheme (programming language)Optimal designMathematical optimizationCost efficiencyEstimation theoryComputer scienceSmall sampleGeneral MedicineSample size determinationStatisticsStatistics Probability and UncertaintyInternal validationcomputercomputer.programming_languageBiometrical Journal
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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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ON THE ASYMPTOTIC DISTRIBUTION OF BARTLETT'S Up-STATISTIC

1985

Abstract. In this paper the asymptotic behaviour of Bartlett's Up-statistic for a goodness-of-fit test for stationary processes, is considered. The asymptotic distribution of the test process is given under the assumption that a central limit theorem for the empirical spectral distribution function holds. It is shown that the Up-statistic tends to the supremum of a tied down Brownian motion. By a counterexample we refute the conjecture that this distribution is in general of the Kolmogorov-Smirnov type. The validity of the central limit theorem for the spectral distribution function is then discussed. Finally a goodness-of-fit test for ARMA-processes based on the estimated innovation sequen…

Statistics and ProbabilityAnderson–Darling testApplied MathematicsMathematical analysisV-statisticAsymptotic distributionKolmogorov–Smirnov testEmpirical distribution functionsymbols.namesakeSampling distributionsymbolsTest statisticStatistics Probability and UncertaintyCentral limit theoremMathematicsJournal of Time Series Analysis
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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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Bayesian analysis and design for comparison of effect-sizes

2002

Comparison of effect-sizes, or more generally, of non-centrality parameters of non-central t distributions, is a common problem, especially in meta-analysis. The usual simplifying assumptions of either identical or non-related effect-sizes are often too restrictive to be appropriate. In this paper, the effect-sizes are modeled as random effects with t distributions. Bayesian hierarchical models are used both to design and analyze experiments. The main goal is to compare effect-sizes. Sample sizes are chosen so as to make accurate inferences about the difference of effect-sizes and also to convincingly solve the testing of equality of effect-sizes if such is the goal.

Statistics and ProbabilityApplied MathematicsBayesian probabilityPosterior probabilityBayes factorRandom effects modelBlock designSample size determinationPrior probabilityStatisticsStatistics Probability and UncertaintyAlgorithmStatistical hypothesis testingMathematicsJournal of Statistical Planning and Inference
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Using mathematical morphology for unsupervised classification of functional data

2011

This paper is concerned with the unsupervised classification of functional data by using mathematical morphology. Different morphological operators are used to extract relevant structures of the functions (considered as sets through their subgraph representations). These operators can be considered as preprocessing tools whose outputs are also functional data. We explore some dissimilarity measures and clustering methods for the classification of the transformed data. Our approach is illustrated through a detailed analysis of two data sets. These techniques, which have mainly been used in image processing, provide a flexible and robust toolbox for improving the results in unsupervised funct…

Statistics and ProbabilityApplied MathematicsData classificationImage processingMathematical morphologycomputer.software_genreToolboxComputingMethodologies_PATTERNRECOGNITIONModeling and SimulationPreprocessorData miningStatistics Probability and UncertaintyCluster analysisMorphological operatorscomputerMathematicsJournal of Statistical Computation and Simulation
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The size of Simes’ global test for discrete test statistics

1999

Abstract To increase the power of the Bonferroni–Holm procedure several modified Bonferroni procedures have been proposed (for example, Hochberg, 1988. Biometrika 75, 800–802; Hommel, 1988. Biometrika 75, 383–386), which are based on Simes’ global test (Simes, 1986. Biometrika 73, 751–754). By several simulation studies which, in particular, considered multinormal test statistics, it has been suggested that the Simes test is a level α test. However, an exact proof exists for only few situations one of them assuming independence of test statistics. We studied the behaviour of Simes’ test for discrete test statistics. Due to discreteness one can expect more conservative decisions whereas depe…

Statistics and ProbabilityApplied MathematicsMultivariate normal distributionNominal levelExact testchemistry.chemical_compoundsymbols.namesakeBonferroni correctionchemistryStatisticsTest statisticsymbolsSign testSIMesStatistics Probability and UncertaintyMathematicsStatistical hypothesis testingJournal of Statistical Planning and Inference
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Optimal signed-rank tests based on hyperplanes

2005

Abstract For analysing k -variate data sets, Randles (J. Amer. Statist. Assoc. 84 (1989) 1045) considered hyperplanes going through k - 1 data points and the origin. He then introduced an empirical angular distance between two k -variate data vectors based on the number of hyperplanes (the so-called interdirections ) that separate these two points, and proposed a multivariate sign test based on those interdirections. In this paper, we present an analogous concept (namely, lift-interdirections ) to measure the regular distances between data points. The empirical distance between two k -variate data vectors is again determined by the number of hyperplanes that separate these two points; in th…

Statistics and ProbabilityApplied MathematicsStudentized residualCombinatoricsRandom variateData pointHyperplaneNorm (mathematics)Test statisticCalculusSign testStatistics Probability and UncertaintyStatistique mathématiqueElliptical distributionMathematics
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