Search results for "Modèle Bayésien"

showing 2 items of 2 documents

Fishery-dependent and -independent data lead to consistent estimations of essential habitats

2016

AbstractSpecies mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Es…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28840Biodiversité et Ecologiehabitatmodélisation spatialehttp://aims.fao.org/aos/agrovoc/c_38371OceanographyGaleus melastomus01 natural sciencesRessource halieutiquehttp://aims.fao.org/aos/agrovoc/c_38127Scyliorhinus caniculamodèle hiérarchiqueSpatial statisticsEcologymodèle de distributionSampling (statistics)Contrast (statistics)Cross-validationModélisation et simulationGeographyHabitatGestion des pêchesModeling and Simulationhttp://aims.fao.org/aos/agrovoc/c_10566http://aims.fao.org/aos/agrovoc/c_3456http://aims.fao.org/aos/agrovoc/c_38117survey designMarine conservationSpecies Distribution ModelsEcology (disciplines)Bayesian probabilityEtmopterus spinaxenquête statistiqueDonnée sur les pêchesmodèle spatiotemporelSede Central IEOContext (language use)Aquatic ScienceDistribution des populationsBayesian hierarchical models010603 evolutionary biologyhttp://aims.fao.org/aos/agrovoc/c_24026elasmobranchsBiodiversity and Ecologyélasmobrancheétude comparativeBayesian hierarchical models;Cross-validation;Species Distribution Models;Spatial statistics;INLA;elasmobranchs ; survey designINLA14. Life underwaterspecies distribution modelsEcology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_6113collecte des donnéesÉcologie marinehttp://aims.fao.org/aos/agrovoc/c_29788http://aims.fao.org/aos/agrovoc/c_4609010604 marine biology & hydrobiologyGestion et conservation des pêchescross validation[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationmodèle bayésienFisheryM01 - Pêche et aquaculture - Considérations généraleshttp://aims.fao.org/aos/agrovoc/c_2a75d27eThéorie bayésienneM40 - Écologie aquatiqueSpatial ecologyhttp://aims.fao.org/aos/agrovoc/c_2942[SDE.BE]Environmental Sciences/Biodiversity and Ecologyvalidation croiséeElasmobranchii
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Epidemiology of Multiple Sclerosis en France

2012

In Europe, France is located between high and low risk areas of Multiple Sclerosis (MS). We estimated the national prevalence of MS in France on 31st October 2004 and the incidence between 2000 and 2007 based on data from the ‘Caisse Nationale d’Assurance Maladie des Travailleurs Salariés’ which insures 87% of the population. MS like other chronic diseases is one of the 30 long-term illnesses (Affections de Longue Durée, ALD). We analysed geographic variations in the prevalence and incidence of MS in France using the Bayesian approach.Total MS prevalence in France standardised for age was 94.7 per 100,000; 130.5 in women; 54.8 in men. The notification rate for MS (2000-2007) after age-stand…

Modèle BayésienMultiple Sclerosis[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyEpidemiology[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyIncidenceBayesian approachSclérose en PlaquesEpidémiologiePrévalence
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