Search results for " Bayesian"
showing 10 items of 124 documents
GW190521: A Binary Black Hole Merger with a Total Mass of 150 M⊙
2020
LIGO Scientific Collaboration and Virgo Collaboration: et al.
Medical news aggregation and ranking of taking into account the user needs
2019
The purpose of this work is to develop an intelligent information system that is designed for aggregation and ranking of news taking into account the needs of the user. The online market for mass media and the needs of readers, the purpose of their searches and moments is not enough to find the news is analyzed. A conceptual model of the information aggression system and ranking of news that would enable presentation of the work of the future intellectual information system, to show its structure is constructed. The methods and means for implementation of the intellectual information system are selected. An online resource for aggregation and ranking of news, news feeds and flexible setting…
Bayesian hierarchical models for analysing the spatial distribution of bioclimatic indices
2017
A methodological approach for modelling the spatial distribution of bioclimatic indices is proposed in this paper. The value of the bioclimatic index is modelled with a hierarchical Bayesian model that incorporates both structured and unstructured random effects. Selection of prior distributions is also discussed in order to better incorporate any possible prior knowledge about the parameters that could refer to the particular characteristics of bioclimatic indices. MCMC methods and distributed programming are used to obtain an approximation of the posterior distribution of the parameters and also the posterior predictive distribution of the indices. One main outcome of the proposal is the …
Radiocarbono y estadística Bayesiana: aportaciones a la cronología de la Edad del Bronce en el extremo oriental del sudeste de la península Ibérica
2014
La investigación arqueológica desarrollada en las últimas décadas ha permitido evaluar que en los valles de los ríos Segura y Vinalopó se dirimió el contacto entre dos sociedades de la Edad del Bronce de la península Ibérica: el grupo Argárico y el grupo del Prebético Meridional Valenciano. Las excavaciones realizadas en tres yacimientos de este ámbito - Terlinques, Cabezo Pardo y Cabezo Redondo- y las dotaciones de radiocarbono obtenidas permiten por primera vez evaluar la diacronía del proceso histórico que envolvió el desarrollo de ambos grupos arqueológicos a lo largo del II milenio cal BC, así como determinar diversos momentos socialmente significativos en su devenir histórico. Para el…
Socio-economic deprivation and COVID-19 infection: a Bayesian spatial modelling approach
2022
Il presente articolo ha l’obiettivo di analizzare l’effetto della deprivazione socio-economica sull’incidenza da COVID-19 a livello sub-comunale. Grazie alla disponibilit`a di informazioni sui tassi di incidenza mensili da COVID-19 a livello di sezione di censimento per i due comuni di Palermo e Catania (Italia), viene pro- posto l’utilizzo di un modello spaziale Bayesiano con distribuzione binomiale zero- inflated. I risultati mostrano un’associazione tra livelli di deprivazione e incidenza da COVID-19 nei due comuni, controllando per la struttura spaziale delle unit`a areali considerate. Alla luce dei risultati, si rendono necessarie azioni di politica sanitaria focalizzando gli intervent…
Whole-Genome Re-Sequencing Data to Infer Historical Demography and Speciation Processes in Land Snails: the Study of Two Candidula Sister Species
2021
Despite the global biodiversity of terrestrial gastropods and their ecological and economic importance, the genomic basis of ecological adaptation and speciation in land snail taxa is still largely unknown. Here, we combined whole-genome re-sequencing with population genomics to evaluate the historical demography and the speciation process of two closely related species of land snails from western Europe, Candidula unifasciata and C. rugosiuscula. Historical demographic analysis indicated fluctuations in the size of ancestral populations, probably driven by Pleistocene climatic fluctuations. Although the current population distributions of both species do not overlap, our approximate Bayesi…
Bayesian versus data driven model selection for microarray data
2014
Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is a particular instance of the model selection problem, i.e., the identification of the correct number of clusters in a dataset. In what follows, for ease of reference, we refer to that instance still as model selection. It is an important part of any statistical analysis. The techniques used for solving it are mainly either Bayesian or data-driven, and are both based on internal knowledge. That is, they use information obtained by processing the input data. A…
Incorporating Uncertainties into Traffic Simulators
2007
Modeling Snow Dynamics Using a Bayesian Network
2015
In this paper we propose a novel snow accumulation and melt model, formulated as a Dynamic Bayesian Network DBN. We encode uncertainty explicitly and train the DBN using Monte Carlo analysis, carried out with a deterministic hydrology model under a wide range of plausible parameter configurations. The trained DBN was tested against field observations of snow water equivalents SWE. The results indicate that our DBN can be used to reason about uncertainty, without doing resampling from the deterministic model. In all brevity, the DBN's ability to reproduce the mean of the observations was similar to what could be obtained with the deterministic hydrology model, but with a more realistic repre…
A Bayesian-optimal principle for learner-friendly adaptation in learning games
2010
Abstract Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predic…