Search results for "bayesian"

showing 4 items of 604 documents

Theoretical and methodological aspects of MCMC computations with noisy likelihoods

2018

Approximate Bayesian computation (ABC) [11, 42] is a popular method for Bayesian inference involving an intractable, or expensive to evaluate, likelihood function but where simulation from the model is easy. The method consists of defining an alternative likelihood function which is also in general intractable but naturally lends itself to pseudo-marginal computations [5], hence making the approach of practical interest. The aim of this chapter is to show the connections of ABC Markov chain Monte Carlo with pseudo-marginal algorithms, review their existing theoretical results, and discuss how these can inform practice and hopefully lead to fruitful methodological developments. peerReviewed

todennäköisyyslaskentabayesilainen menetelmälikelihoodsBayesian computationStatistics::Computation
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Características de los vecindarios y la distribución espacial de problemas sociales en la ciudad de Valencia

2018

The aim of this doctoral thesis is to explore the influence of neighborhood-level variables on the spatial and spatio-temporal distribution of different social problems in the city of Valencia. In Study 1, we present data on the development and validation of an observational instrument to assess neighborhood disorder. Results supported a three-factor model (physical disorder, social disorder and physical deterioration), and they showed good reliability and validity evidences. In Study 2, we assess the psychometric properties of a neighborhood disorder scale using Google Street View. Results supported a bifactorial solution with a general factor (general neighborhood disorder) and two specif…

vecindariosdesorden del vecindarioventa de bebidas alcohólicasintervenciones policiales por drogas:PSICOLOGÍA [UNESCO]modelos bayesianos espacialesUNESCO::PSICOLOGÍAllamadas policiales por suicidioviolencia familiar
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Vai strukturālās reformas spēs veicināt Latvijas ekonomisko izaugsmi: BMA un GMM novērtējumu liecības

2017

Pētījuma ietvaros tiek pielietota Beijesa modeļu svēršana (BMA) un vispārīgā momentu metode (GMM) Globālās Konkurētspējas apakšindeksu (GCI) datiem, lai identificētu strukturālo reformu jomas, kas var nozīmīgi paātrināt Latvijas ekonomisko izaugsmi. Novērtējumu rezultāti, kuros ņemta vērā gan modeļu nenoteiktība, gan endogenitāte liecina, ka ekonomisko izaugsmi var veicināt ar augstākām investīcijām, zemāku administratīvo slogu, stabilāku makroekonomisko vidi, paaugstinātu ārvalsts tiešo investīciju kvalitāti, kā arī ar attīstītākiem uzņēmējdarbības klasteriem. Ja šajās jomās Latvijas sniegums pēdējo 10 gadu laikā būtu trīs labāko Eiropas Savienības dalībvalstu līmenī, tad ienākumu līmenis …

vispārīgā momentu metodestrukturālās reformasEkonomikaGeneralized Method of MomentsBeijesa modeļu svēršanaBayesian Model Averaging
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Inferring phytoplankton community composition with a fatty acid mixing model

2015

Abstract. The taxon specificity of fatty acid composition in algal classes suggests that fatty acids could be used as chemotaxonomic markers for phytoplankton composition. The applicability of phospholipid-derived fatty acids as chemotaxonomic markers for phytoplankton composition was evaluated by using a Bayesian fatty acid-based mixing model. Fatty acid profiles from monocultures of chlorophytes, cyanobacteria, diatoms, euglenoids, dinoflagellates, raphidophyte, cryptophytes and chrysophytes were used as a reference library to infer phytoplankton community composition in five moderately humic, large boreal lakes in three different seasons (spring, summer and fall). The phytoplankton commu…

zooplanktonFASTARseasonalityfungichemotaxonomic markerBayesian mixing modelfood qualityfreshwater phytoplanktonlevätpolyunsaturated fatty acid
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