Search results for "Mixed"

showing 10 items of 783 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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On Rao Score and Pearson X2 Statistics in Generalized Linear Models

2005

The identity of the Rao score and PearsonX 2 statistics is well known in the areas where the latter was first introduced: goodness-of-fit in contingency tables and binary responses. We show in this paper that the same identity holds when the two statistics are used for testing goodness-of-fit of Generalized Linear Models. We also highlight the connections that exist between the two statistics when they are used for the comparison of nested models. Finally, we discuss some merits of these unifying results.

Statistics and ProbabilityContingency tableProper linear modelstatisticLinear modelScoreRao scoreGeneralized linear mixed modelHierarchical generalized linear modelQuasi-likelihoodStatisticsStatistics Probability and Uncertaintylinear modelsGeneralized estimating equationMathematics
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Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models

2021

In ecological community studies it is often of interest to study the effect of species related trait variables on abundances or presence-absences. Specifically, the interest may lay in the interactions between environmental and trait variables. An increasingly popular approach for studying such interactions is to use the so-called fourth-corner model, which explicitly posits a regression model where the mean response of each species is a function of interactions between covariate and trait predictors (among other terms). On the other hand, many of the fourth-corner models currently applied in the literature are too simplistic to properly account for variation in environmental and trait resp…

Statistics and ProbabilityEcological ModelingLatent variableeliöyhteisötcommunity analysisGeneralized linear mixed modelekologiajoint species distribution modelgeneralized linear mixed modelmultivariate abundance datamonimuuttujamenetelmätCommunity analysisEconometricsTraitvariational approximationtilastolliset mallitfourth-corner problemympäristönmuutoksetMathematics
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Financial distress and real economic activity in Lithuania: a Granger causality test based on mixed-frequency VAR

2020

In this paper, we extend the monthly financial stress index for Lithuania, computed by the European Central Bank, to a daily frequency and we also include banking sector stress among its constituents, beyond bond, equity and foreign exchange markets. We investigate the causal relationship between the daily financial stress index and monthly industrial production growth, using a Granger causality test applied to a mixed-frequency VAR. Our results suggest evidence of Granger causality from financial stress to industrial production growth once the index is enriched by daily observations from the financial markets. Our findings, based on impulse response analysis, confirm the negative effect of…

Statistics and ProbabilityEconomics and EconometricsMixed frequencyIndustrial productionBond05 social sciencesFinancial marketEquity (finance)Mathematics (miscellaneous)Granger causalityFinancial stress index0502 economics and businessEconometricsEconomicsGranger causalityFinancial distress050207 economicsReal economyMixed frequency dataSocial Sciences (miscellaneous)050205 econometrics
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Balanced Asymmetrical Nearly Orthogonal Designs for first and second order effect estimation

2006

Abstract A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interaction estimability requirements with a number of runs as small as possible, is proposed in this paper. The method, based on a heuristic procedure, uses a new optimality criterion formulated here. The proposed method demonstrates efficiency in terms of searching time and optimality of the attained designs. A complete collection of such asymmetrical designs with two- and three-level factors is available. A technological application is also presented.

Statistics and ProbabilityEstimationMathematical optimizationOptimality criterionSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaOrder effectStatistics Probability and UncertaintyHeuristic procedureBalancing asymmetrical (mixed-level) designs nearly orthogonal arrays optimality two- and three-level designsMathematicsJournal of Applied Statistics
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Subject-specific odds ratios in binomial GLMMs with continuous response

2007

In a regression context, the dichotomization of a continuous outcome variable is often motivated by the need to express results in terms of the odds ratio, as a measure of association between the response and one or more risk factors. Starting from the recent work of Moser and Coombs (Odds ratios for a continuous outcome variable without dichotomizing, Statistics in Medicine, 2004, 23, 1843-1860), in this article we explore in a mixed model framework the possibility of obtaining odds ratio estimates from a regression linear model without the need of dichotomizing the response variable. It is shown that the odds ratio estimators derived from a linear mixed model outperform those from a binom…

Statistics and ProbabilityGeneral linear modelProper linear modelDichotomizingBinomial regressionLinear modelLogistic regressionOdds ratioEfficiencyRandom effects modelLogistic regressionGeneralized linear mixed modelRandom effectStatisticsEconometricsDiagnostic odds ratioStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaMathematics
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Modeling Posidonia oceanica growth data: from linear to generalized linear mixed models

2010

The statistical analysis of annual growth of Posidonia oceanica is traditionally carried out through Gaussian linear models applied to untransformed, or log-transformed, data. In this paper, we claim that there are good reasons for re-considering this established practice, since real data on annual growth often violate the assumptions of Gaussian linear models, and show that the class of Generalized Linear Models (GLMs) represents a useful alternative for handling such violations. By analyzing Sicily PosiData-1, a real dataset on P. oceanica growth data gathered in the period 2000–2002 along the coasts of Sicily, we find that in the majority of cases Normality is rejected and the effect of …

Statistics and ProbabilityGeneralized linear modelSettore BIO/07 - EcologiabiologyEcological Modelingmedia_common.quotation_subjectGaussianLinear modelPosidonia oceanica annual growth Generalized Linear Models Generalized Linear Mixed Models lepidochronological data.biology.organism_classificationGeneralized linear mixed modelHierarchical generalized linear modelsymbols.namesakePosidonia oceanicaStatisticsEconometricsGamma distributionsymbolsSettore SECS-S/01 - StatisticaNormalityMathematicsmedia_common
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A differential-geometric approach to generalized linear models with grouped predictors

2016

We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important properties that distinguish it from the group lasso. First, its solution curve is based on the invariance properties of a generalized linear model. Second, it adds groups of variables based on a group equiangularity condition, which is shown to be related to score statistics. An adaptive version, which includes weights based on the Kullback-Leibler divergence, improves its variable selection fea…

Statistics and ProbabilityGeneralized linear modelStatistics::TheoryMathematical optimizationProper linear modelGeneral MathematicsORACLE PROPERTIESGeneralized linear modelSPARSITYGeneralized linear array model01 natural sciencesGeneralized linear mixed modelCONSISTENCY010104 statistics & probabilityScore statistic.LEAST ANGLE REGRESSIONLinear regressionESTIMATORApplied mathematicsDifferential geometry0101 mathematicsDivergence (statistics)MathematicsVariance functionDifferential-geometric least angle regressionPATH ALGORITHMApplied MathematicsLeast-angle regressionScore statistic010102 general mathematicsAgricultural and Biological Sciences (miscellaneous)Group lassoGROUP SELECTIONStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesSettore SECS-S/01 - Statistica
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Bayesian assessment of times to diagnosis in breast cancer screening

2008

Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.

Statistics and ProbabilityHyperparametermedicine.diagnostic_testbusiness.industryComputer scienceMarkov chain Monte CarloMachine learningcomputer.software_genreBayesian inferencemedicine.diseaseGeneralized linear mixed modelBayesian statisticsBreast cancer screeningsymbols.namesakeBreast cancerStatisticsmedicinesymbolsMammographyArtificial intelligenceStatistics Probability and UncertaintybusinesscomputerJournal of Applied Statistics
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Pairwise Markov properties for regression graphs

2016

With a sequence of regressions, one may generate joint probability distributions. One starts with a joint, marginal distribution of context variables having possibly a concentration graph structure and continues with an ordered sequence of conditional distributions, named regressions in joint responses. The involved random variables may be discrete, continuous or of both types. Such a generating process specifies for each response a conditioning set that contains just its regressor variables, and it leads to at least one valid ordering of all nodes in the corresponding regression graph that has three types of edge: one for undirected dependences among context variables, another for undirect…

Statistics and ProbabilityMarkov chain010102 general mathematicsMixed graphConditional probability distribution01 natural sciencesCombinatorics010104 statistics & probabilityConditional independenceJoint probability distributionMarkov property0101 mathematicsStatistics Probability and UncertaintyMarginal distributionRandom variableMathematicsStat
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