Search results for "Bayesian framework"

showing 3 items of 3 documents

Nonlinear impact estimation in spatial autoregressive models

2018

International audience; This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in…

Economics and Econometrics[SDV]Life Sciences [q-bio]Lag0507 social and economic geographysymbols.namesake0502 economics and businessEconometricsMarginal impacts050207 economicsSpatial econometricsMathematics05 social sciencesMarkov chain Monte Carlo[SHS.ECO]Humanities and Social Sciences/Economics and FinanceSplineConfidence intervalMarkov chain Monte CarloSpline (mathematics)Nonlinear systemAutoregressive model13. Climate actionsymbolsBayesian frameworkSpatial econometrics050703 geographyFinanceEconomics Letters
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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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Use of hierarchical Bayesian framework in MTS studies to model different causes and novel possible forms of acquired MTS

2015

Abstract: An integrative account of MTS could be cast in terms of hierarchical Bayesian inference. It may help to highlight a central role of sensory (tactile) precision could play in MTS. We suggest that anosognosic patients, with anesthetic hemisoma, can also be interpreted as a form of acquired MTS, providing additional data for the model.

business.industryCognitive NeuroscienceTOUCHBODY AWARENESSSensory systemTactile perceptionBody awarenessBayesian inferenceMachine learningcomputer.software_genreHiearchical Bayesian ModelIllusionTouch PerceptionTactile PerceptionSYNAESTHESIABayesian frameworkArtificial intelligencePerceptual DisorderbusinessPsychologycomputerHumanCognitive Neuroscience
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