Search results for " Inference"

showing 10 items of 337 documents

WEIGHTED-AVERAGE LEAST SQUARES (WALS): A SURVEY

2014

Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted- average least squares (WALS) is a recent model-average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications.

Economics and EconometricsModel selection05 social sciencesBayesian probability01 natural sciencesLeast squares010104 statistics & probabilityFrequentist inferencePosition (vector)0502 economics and businessStatisticsPrior probability0101 mathematicsWeighted arithmetic mean050205 econometrics MathematicsJournal of Economic Surveys
researchProduct

Sampling properties of the Bayesian posterior mean with an application to WALS estimation

2022

Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these learning methods in repeated samples is assessed using the variance of the posterior distribution of the parameters of interest given the data. This may be permissible when the sample size is large because, under the conditions of the Bernstein--von Mises theorem, the posterior variance agrees asymptotically with the frequentist variance. In finite samples, however, things are less clear. In this pa…

Economics and EconometricsWALS.SDG 16 - PeaceSettore SECS-P/05Monte Carlo methodBayesian probabilityPosterior probabilitySettore SECS-P/05 - EconometriaDouble-shrinkage estimators01 natural sciencesLeast squares010104 statistics & probabilityFrequentist inference0502 economics and businessStatisticsPosterior moments and cumulantsStatistics::Methodology0101 mathematicsdouble-shrinkage estimator050205 econometrics MathematicsWALSLocation modelApplied Mathematics05 social sciencesSDG 16 - Peace Justice and Strong InstitutionsUnivariateSampling (statistics)EstimatorVariance (accounting)/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsJustice and Strong InstitutionsSample size determinationposterior moments and cumulantNormal location modelJournal of Econometrics
researchProduct

Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging

2021

En este artículo analizamos los determinantes del stock de FDI saliente de Japón para el período 1996–2017. Este período es especialmente relevante ya que abarca un proceso de creciente globalización económica y dos crisis financieras. Para ello, consideramos un amplio conjunto de variables candidatas basadas en la teoría, así como en análisis empíricos previos. Nuestra muestra incluye un total de 27 países anfitriones. Seleccionamos las covariables utilizando una metodología basada en datos, el análisis Bayesian Model Averaging (BMA). Además, también analizamos si estos determinantes cambian según el grado de desarrollo (emergentes vs desarrollados) o las áreas geográficas (UE vs Asia Orie…

Economics and Econometricsfinancial developmentHorizontal and verticalforeign direct investmentSample (statistics)Foreign direct investmentBayesian inferenceEconomic globalization:CIENCIAS ECONÓMICAS [UNESCO]0502 economics and businessinstitutional qualityEconomicsEast Asia050207 economicsEmerging marketsStock (geology)040101 forestryFinancebusiness.industry05 social sciencesUNESCO::CIENCIAS ECONÓMICAS04 agricultural and veterinary sciencesjapangravitybayesian model averagingPolitical Science and International Relations0401 agriculture forestry and fisheriesbusinessFinanceJapan and the World Economy
researchProduct

Unawareness and Partitional Information Structures

1999

Abstract We claim first that simple uncertainty is not an adequate model of a subject's ignorance, because a major component of it is the inability to give a complete description of the states of the world, and we provide a formal model of unawareness. In Modica and Rustichini (1994) we showed a difficulty in the project, namely that without weakening of the inference rules of the logic one would face the unpleasant alternative between full awareness and full unawareness. In this paper we study a logical system where non full awareness is possible, and prove that a satisfactory solution to the problem can be found by introducing limited reasoning ability of the subject. A determination theo…

Economics and Econometricsmedia_common.quotation_subjectComponent (UML)Subject (grammar)Limited reasoning abilityIgnoranceRule of inferenceMathematical economicsFinancemedia_commonMathematicsSimple (philosophy)Games and Economic Behavior
researchProduct

An entropy-based machine learning algorithm for combining macroeconomic forecasts

2019

This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.

Elastic net regularizationKullback–Leibler divergenceComputer scienceGeneral Physics and AstronomyInferencelcsh:Astrophysics02 engineering and technologyMachine learningcomputer.software_genremaximum-entropy inferenceArticleGDPGross domestic productlcsh:QB460-4660502 economics and business0202 electrical engineering electronic engineering information engineeringEntropy (information theory)lcsh:Science050205 econometrics combining predictionsaveragingMacroeconomiabusiness.industry05 social scienceslcsh:QC1-999Economia matemàticaTecnologiaKullback–Leiblerlcsh:Q020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerAlgorithmlcsh:Physics
researchProduct

Broken rotor bars detection via Park's vector approach based on ANFIS

2014

Many attempts have been made on fault diagnosis of induction motors based on frequency and time domain analysis of stator current. In this paper, first the Park's vector transformation and frequency analysis for fault detection of induction motors are introduced. Then a smart approach using Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed. This approach uses the time domain features derived from the Park's vector transformation of stator current. By the proposed method, a partial break including 5 mm crack on a bar, one broken bar and two broken bars using experimental data are investigated. It will be shown that features derived from Park's vector compared to features obtained fro…

EngineeringAdaptive neuro fuzzy inference systemRotor (electric)business.industryStatorANFIS; broken rotor bars; fault diagnosis; Park's transformation; Electrical and Electronic Engineering; Control and Systems EngineeringCoordinate vectorfault diagnosisFault (power engineering)Fault detection and isolationlaw.inventionlawControl theoryControl and Systems EngineeringTime domainElectrical and Electronic EngineeringbusinessANFISbroken rotor barsPark's transformationInduction motor
researchProduct

Adaptive neural-fuzzy inference system based method to modeling of vehicle crash

2013

Various areas of research need to be considered in order to establish a mathematical model of a vehicle crash. To enhance the modeling process, a novel ANFIS-based approach to reconstruct behavior of impacting vehicles is presented in this paper. Kinematics of center of gravity (COG) a vehicle involved in an oblique barrier collision is reproduced by application of a five-layered ANFIS structure. Then, the same ANFIS system is used to simulate a different collision type than the one which was used in the training stage. The points of interests are selected to be the locations of accelerometers mounting. The accuracy of the proposed method is evaluated by the comparative analysis with the re…

EngineeringCenter of gravityAdaptive neuro fuzzy inference systembusiness.industryProcess (computing)Oblique caseControl engineeringStage (hydrology)KinematicsbusinessCollisionAccelerometerSimulation2013 IEEE International Conference on Mechatronics (ICM)
researchProduct

Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling

2011

Abstract Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessm…

EngineeringEnvironmental Engineering* MCMCRainmedia_common.quotation_subjectBayesian probability* Parameter probability distributionBayesian inferencecomputer.software_genre* MICAsymbols.namesake* GLUEWater QualityStatistics* Bayesian inferenceComputer SimulationQuality (business)CitiesGLUEWaste Management and Disposal* Urban drainage modelWater Science and TechnologyCivil and Structural Engineeringmedia_common* SCEM-UALikelihood Functions* Multi-objective auto-calibrationSettore ICAR/03 - Ingegneria Sanitaria-Ambientalebusiness.industryEcological ModelingUncertaintyMarkov chain Monte CarloModels TheoreticalPollutionMarkov ChainsRunoff model* UncertaintieMetropolis–Hastings algorithmsymbolsProbability distribution* AMALGAMData miningbusinessMonte Carlo MethodcomputerAlgorithmsSoftware
researchProduct

A fuzzy logic approach to modeling a vehicle crash test

2013

Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0032-2 This paper presents an application of fuzzy approach to vehicle crash modeling. A typical vehicle to pole collision is described and kinematics of a car involved in this type of crash event is thoroughly characterized. The basics of fuzzy set theory and modeling principles based on fuzzy logic approach are presented. In particular, exceptional attention is paid to explain the methodology of creation of a fuzzy model of a vehicle collision. Furthermore, the simulation results are presented and compared to the original vehic…

EngineeringEnvironmental Engineeringmedia_common.quotation_subjectFuzzy setAerospace EngineeringFidelityCrashKinematicsFuzzy logicGeneral Materials Sciencevehicle crashElectrical and Electronic EngineeringCivil and Structural Engineeringmedia_commonAdaptive neuro fuzzy inference systemEvent (computing)business.industryMechanical EngineeringVDP::Technology: 500::Mechanical engineering: 570modelingControl engineeringEngineering (General). Civil engineering (General)Collisionfuzzy logicTA1-2040businessOpen Engineering
researchProduct

Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…

2012

Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…

EngineeringIntegrated urban drainage systemSettore ICAR/03 - Ingegneria Sanitaria-Ambientalebusiness.industryWastewater treatment plantBayesian probabilityBayesian inferencePower transformBayesian inferenceGeophysicsGeochemistry and PetrologyHomoscedasticityStatisticsWater-quality modellingEconometricsGeneralised Likelihood Uncertainty Estimation (GLUE)Sensitivity analysisReceiving water bodybusinessLikelihood functionGLUEUncertainty analysis
researchProduct