Results 51 to 60 of about 3,561,036 (197)
A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA) [PDF]
, 2011 "The authors also gratefully acknowledge the financial support of Research Councils UK for Illian"This paper develops methodology that provides a toolbox for routinely fitting complex models to realistic spatial point pattern data.
Illian, Janine Baerbel +7 more
core +1 more source
A Bayesian Spatial Disaggregation Approach for Fine‐Scale Mapping of Water Access Disparities
Sustainable Development, EarlyView.ABSTRACT Access to clean water remains a critical challenge for achieving Sustainable Development Goal 6: Clean Water and Sanitation. While national statistics agencies report water access at coarse municipal scales, this data obscure critical hotspots where vulnerable populations lack essential services.
Ivan Lizarazo +2 more
wiley +1 more source
, 2018 © 2017, © 2017 Taylor & Francis Group, LLC. The combined model accounts for different forms of extra-variability and has traditionally been applied in the likelihood framework, or in the Bayesian setting via Markov chain Monte Carlo.
Thomas Neyens +6 more
core +1 more source
Spatial analysis of bluetongue cases and vaccination of Swiss cattle in 2008 and 2009
Geospatial Health, 2011 Bluetongue (BT) is a vector-borne viral disease of ruminants. The infection is widespread globally with major implications for international animal trade and production.
Katriina J. E. Willgert +2 more
doaj +1 more source
Can AI be Easy? Lessons Learned From the EZR.py Toolkit
Software: Practice and Experience, EarlyView.ABSTRACT Much recent press claims that developers no longer need to read code. We disagree, at least within the domain of tabular software‐engineering (SE) optimization tasks: rows of x$$ x $$ and y$$ y $$ values where the y$$ y $$ values are expensive to obtain.
Tim Menzies +2 more
wiley +1 more source
Modelling and Inference for Bayesian Bivariate Animal Models using Integrated Nested Laplace Approximations [PDF]
, 2014 In this study we focus on performing inference on bivariate animal models using Integrated Nested Laplace Approximation (INLA). INLA is a methodology for making fast non-sampling based Bayesian inference for hierarchical Gaussian Markov models.
Bøhn, Eirik Dybvik
core +1 more source
A Bayes factor framework for unified parameter estimation and hypothesis testing
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Bayes factor, the data‐based updating factor of the prior to posterior odds of two hypotheses, is a natural measure of statistical evidence for one hypothesis over the other. We show how Bayes factors can also be used for parameter estimation.
Samuel Pawel
wiley +1 more source
Methods in Ecology and Evolution, 2023 Ecological data are being collected at a large scale from a multitude of different sources, each with their own sampling protocols and assumptions. As a result, the integration of disparate datasets is a rapidly growing area in quantitative ecology, and ...
Philip S. Mostert, Robert B. O'Hara
doaj +1 more source
Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
wiley +1 more source
Using Integrated Nested Laplace Approximations for Modelling Spatial Healthcare Utilization
, 2012 In recent years, spatial and spatio-temporal modeling have become an important area of research in many fields (epidemiology, environmental studies, disease mapping). In this work we propose different spatial models to study hospital recruitment, including some potentially explicative variables.
MUSIO, MONICA +2 more
openaire +4 more sources