Search results for "MODEL SELECTION"

showing 10 items of 64 documents

A generalized predictive criterion for model selection

2002

Given a random sample from some unknown model belonging to a finite class of parametric models, assume that the estimate of the density of a future observation is of interest San Martini & Spezzaferri (1984) proposed for this problem a predictive criterion based on the logarithmic utility function. The present authors investigate a generalization of this criterion that uses as a loss function an element of the class of α-divergences discussed by Ali & Silvey (1966) and Csiszar (1967). They also discuss briefly the case in which the class of models considered is not exhaustive. Un critere de prevision generalise pour la selection de modeles Supposons que l'on cherche a estimer la densite d'u…

Statistics and ProbabilityCombinatoricsmodel selectionModel selectionCalculusloss function; model selection; α-divergencesStatistics Probability and Uncertaintyα-divergencesMathematicsloss function
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The Effective Sample Size

2013

Model selection procedures often depend explicitly on the sample size n of the experiment. One example is the Bayesian information criterion (BIC) criterion and another is the use of Zellner–Siow priors in Bayesian model selection. Sample size is well-defined if one has i.i.d real observations, but is not well-defined for vector observations or in non-i.i.d. settings; extensions of critera such as BIC to such settings thus requires a definition of effective sample size that applies also in such cases. A definition of effective sample size that applies to fairly general linear models is proposed and illustrated in a variety of situations. The definition is also used to propose a suitable ‘sc…

Deviance information criterionEconomics and EconometricsBayesian information criterionSample size determinationModel selectionPrior probabilityStatisticsLinear modelBayesian inferenceAlgorithmSelection (genetic algorithm)Statistics::ComputationMathematicsEconometric Reviews
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Pure donation or hybrid donation crowdfunding

2019

PurposeDespite the growing research exploring the possibility and feasibility of financing socially oriented projects through crowdfunding, relatively little research examines which crowdfunding model is better to serve such purpose. The purpose of this paper is to offer novel insights to mitigate this research gap.Design/methodology/approachA unique data set collected from the largest Chinese crowdfunding platform is used to test the hypotheses. To solve the perceived self-selection problem, the propensity score matching method is adopted in this paper. Based on this approach, the results of similar prosocial campaigns in two different models (pure donation and hybrid donation) are compare…

MarketingCognitive evaluation theoryOrganizational Behavior and Human Resource ManagementStrategy and ManagementModel selection05 social sciencesProbability of successProsocial behaviorNegatively associatedManagement of Technology and InnovationDonation0502 economics and businessPropensity score matching050207 economicsBusiness and International ManagementMarketingPsychology050203 business & managementBaltic Journal of Management
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Wind Speed Forecasting by Box-Jenkins Models

2008

The possibility of modelling observed wind speed time series and forecasting their future values is presented in this paper. Seasonal autoregressive integrated moving average (SARIMA) models are applied to time series formed by four years hourly average wind speed measurements in thirty sites of Sicily. Our approach is considerably different from the original one (the Box-Jenkins approach) since it is completely automatic. We use a peculiar feature of wind speed on a land area, its daily period, to identify a class of SARIMA models within which to find the best fitting model by information criteria (here we employ AICC). Here we report the results, concerning the fit and forecast accuracy, …

Wind forecastingSpectral analysiStochastic modelTime serieModel selection
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Spatial autocorrelation and the selection of simultaneous autoregressive models

2007

Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and inference from statistical models. Here, we test the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err , lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial autocorrelation structures. Methods We evaluate the performance of SAR models by examining spatial patterns in model residuals (with correlograms and residual maps), by comparing model para…

Global and Planetary ChangeEcologyEcologyModel selectionfungiAutocorrelationStatistical modelResidualbody regionsAutoregressive modelStatisticsSpatial ecologyAkaike information criterionskin and connective tissue diseasesSpatial analysisEcology Evolution Behavior and SystematicsMathematicsGlobal Ecology and Biogeography
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Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy

2008

Flexible survival models, which avoid assumptions about hazards proportionality (PH) or linearity of continuous covariates effects, bring the issues of model selection to a new level of complexity. Each ‘candidate covariate’ requires inter-dependent decisions regarding (i) its inclusion in the model, and representation of its effects on the log hazard as (ii) either constant over time or time-dependent (TD) and, for continuous covariates, (iii) either loglinear or non-loglinear (NL). Moreover, ‘optimal’ decisions for one covariate depend on the decisions regarding others. Thus, some efficient model-building strategy is necessary. We carried out an empirical study of the impact of the model …

MaleStatistics and ProbabilityEpidemiologyAge at diagnosisAdenocarcinomaEmpirical researchRisk FactorsStomach NeoplasmsCovariateStatisticsEconometricsHumansRegistriesSurvival analysisAgedParametric statisticsMathematicsModels StatisticalModel selectionMultivariable calculusAge FactorsMiddle AgedPrognosisSurvival AnalysisMultivariate AnalysisFemaleFranceLog-linear modelStatistics in Medicine
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Two-Stage Bayesian Approach for GWAS With Known Genealogy

2019

Genome-wide association studies (GWAS) aim to assess relationships between single nucleotide polymorphisms (SNPs) and diseases. They are one of the most popular problems in genetics, and have some peculiarities given the large number of SNPs compared to the number of subjects in the study. Individuals might not be independent, especially in animal breeding studies or genetic diseases in isolated populations with highly inbred individuals. We propose a family-based GWAS model in a two-stage approach comprising a dimension reduction and a subsequent model selection. The first stage, in which the genetic relatedness between the subjects is taken into account, selects the promising SNPs. The se…

0301 basic medicineStatistics and ProbabilityBayesian probabilityPopulationSingle-nucleotide polymorphismGenome-wide association studyComputational biologyEstadísticaBiologyKinship coefficientModel selection01 natural sciencesBeta-thalassemia010104 statistics & probability03 medical and health sciencesBeta-thalassemia disorderModelsRobust prior distributionRegularizationDiscrete Mathematics and Combinatorics0101 mathematicsStage (cooking)Genetic associationGenome-wide associationModel selectionVariable-selectionProbability and statisticsBayes factorRegressionBayes factor030104 developmental biologyPhenotypeStatistics Probability and UncertaintyGaussian Markov random field
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Contributed discussion on article by Pratola

2016

The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.

Statistics and Probabilitymodel selectionMarkov Chain Monte Carlo (MCMC)Bayesian regression treeComputer scienceBig dataBayesian regression tree (BRT) modelsComputingMilieux_LEGALASPECTSOFCOMPUTINGbirth–death processMachine learningcomputer.software_genreSequential Monte Carlo methods01 natural sciencespopulation Markov chain Monte Carlo010104 statistics & probabilitysymbols.namesakebig data0502 economics and businessBayesian Regression Trees (BART)0101 mathematics050205 econometrics Bayesian treed regressionMultiple Try Metropolis algorithmsINFERÊNCIA ESTATÍSTICAbusiness.industryApplied MathematicsModel selection05 social sciencesRejection samplingData scienceVariable-order Bayesian networkTree (data structure)Tree traversalMarkov chain Monte Carlocontinuous time Markov processsymbolsArtificial intelligencebusinessBayesian linear regressioncommunication-freecomputerGibbs samplingBayesian Analysis
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Detection of Allee effects in marine fishes: analytical biases generated by data availability and model selection

2017

The demographic Allee effect, or depensation, implies positive association between per capita population growth rate and population size at low abundances, thereby lowering growth ability of sparse populations. This can have far-reaching consequences on population recovery ability and colonization success. In the context of marine fishes, there is a widespread perception that Allee effects are rare or non-existent. However, studies that have failed to detect Allee effects in marine fishes have suffered from several fundamental methodological and data limitations. In the present study, we challenge the prevailing perception about the rarity of Allee effects by analysing nine populations of …

0106 biological sciencesPopulation DynamicsAtlantic herringBiologyModels Biological010603 evolutionary biology01 natural sciencesPopulation densityGeneral Biochemistry Genetics and Molecular BiologycompensationDepensationsymbols.namesakePer capitaAnimalsPopulation growth14. Life underwaterClupea harengusPopulation GrowthGeneral Environmental ScienceAllee effectlow-abundance dynamicsPopulation DensityModels StatisticalEcologyGeneral Immunology and MicrobiologyEcology010604 marine biology & hydrobiologyModel selectionPopulation sizestock–recruitment relationshipFishesBayes TheoremGeneral MedicineData availabilitydepensationsymbolsta1181General Agricultural and Biological SciencesProceedings of the Royal Society B: Biological Sciences
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Model comparison and selection for stationary space–time models

2007

An intensive simulation study to compare the spatio-temporal prediction performances among various space-time models is presented. The models having separable spatio-temporal covariance functions and nonseparable ones, under various scenarios, are also considered. The computational performance among the various selected models are compared. The issue of how to select an appropriate space-time model by accounting for the tradeoff between goodness-of-fit and model complexity is addressed. Performances of the two commonly used model-selection criteria, Akaike information criterion and Bayesian information criterion are examined. Furthermore, a practical application based on the statistical ana…

Statistics and ProbabilityMathematical optimizationCovariance functionbusiness.industryApplied MathematicsModel selectionMultilevel modelKalman filterCovarianceMachine learningcomputer.software_genreComputational MathematicsComputational Theory and MathematicsGoodness of fitBayesian information criterionArtificial intelligenceAkaike information criterionbusinesscomputerMathematicsComputational Statistics & Data Analysis
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