A spliced Gamma-Generalized Pareto model for short-term extreme wind speed probabilistic forecasting [PDF]
, 2019 Renewable sources of energy such as wind power have become a sustainable alternative to fossil fuel-based energy. However, the uncertainty and fluctuation of the wind speed derived from its intermittent nature bring a great threat to the wind power ...
Castro-Camilo, Daniela +2 more
core +2 more sources
A Bayesian space–time model for clustering areal units based on their disease trends [PDF]
, 2018 Population-level disease risk across a set of non-overlapping areal units varies in space and time, and a large research literature has developed methodology for identifying clusters of areal units exhibiting elevated risks.
Lawson, Andrew +3 more
core +2 more sources
Modelación de la sobrepoblación relativa en localidades de Chiapas: análisis espacial bayesiano
Economía, Sociedad y Territorio, 2023 El objetivo de este trabajo es identificar patrones de distribución espacial de la sobrepoblación relativa, medida por la Población Económicamente Activa y la migración, en localidades del estado de Chiapas en 2020.
Cuauhtémoc Calderón Villarreal +2 more
doaj +1 more source
The rational SPDE approach for Gaussian random fields with general smoothness [PDF]
, 2019 A popular approach for modeling and inference in spatial statistics is to represent Gaussian random fields as solutions to stochastic partial differential equations (SPDEs) of the form $L^{\beta}u = \mathcal{W}$, where $\mathcal{W}$ is Gaussian white ...
Bolin, David, Kirchner, Kristin
core +2 more sources
Benefits of spatio-temporal modelling for short term wind power forecasting at both individual and aggregated levels [PDF]
, 2017 The share of wind energy in total installed power capacity has grown rapidly in recent years around the world. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is essential to ...
Ackermann +43 more
core +3 more sources
Scientific Reports, 2021 Occupational and environmental associations with systemic sclerosis (SSc) have been confirmed; however, the association between aerosol components and mortality is uncertain.
Chingching Foocharoen +4 more
doaj +1 more source
Approximate Bayesian Model Selection with the Deviance Statistic [PDF]
, 2015 Bayesian model selection poses two main challenges: the specification of parameter priors for all models, and the computation of the resulting Bayes factors between models.
Bové, Daniel Sabanés +2 more
core +1 more source
Bayesian Computing with INLA: A Review [PDF]
, 2016 The key operation in Bayesian inference is to compute high-dimensional integrals. An old approximate technique is the Laplace method or approximation, which dates back to Pierre-Simon Laplace (1774).
Bolin D +8 more
core +2 more sources
Discrete versus continuous domain models for disease mapping [PDF]
, 2019 The main goal of disease mapping is to estimate disease risk and identify high-risk areas. Such analyses are hampered by the limited geographical resolution of the available data.
Konstantinoudis, Garyfallos +3 more
core +2 more sources
meta4diag: Bayesian Bivariate Meta-Analysis of Diagnostic Test Studies for Routine Practice
Journal of Statistical Software, 2018 This paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of diagnostic test studies. Our package meta4diag is a purpose-built front end of the R package INLA.
Jingyi Guo, Andrea Riebler
doaj +1 more source