Article
Statistics & Probability
David Bolin, Alexandre B. Simas, Zhen Xiong
Summary: The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. A new method is proposed for Bayesian inference using a stable Gaussian Markov random fields (GMRF) approximation, which approximates the covariance operator of the Gaussian field by a finite element method combined with a rational approximation of the fractional power. The method is rigorously analyzed for convergence and the accuracy is investigated with simulated data.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Janet Van Niekerk, Elias Krainski, Denis Rustand, Havard Rue
Summary: Integrated Nested Laplace Approximations (INLA) is a successful approximate Bayesian inference framework that offers increased computational efficiency and accuracy compared to sampling-based methods such as MCMC. Ongoing research and implementation in R-INLA ensure its continued relevance and improved performance and applicability. The era of big data presents an opportunity to reformulate aspects of the classic INLA formulation for faster inference, improved numerical stability, and scalability, particularly for data-rich models. Various examples demonstrate the efficiency gains in tangible ways.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2023)
Article
Engineering, Environmental
Somnath Chaudhuri, Pablo Juan, Laura Serra Saurina, Diego Varga, Marc Saez
Summary: Natural hazards have significant impacts on the environment and society, causing damage to life and property. Computational modeling is an essential tool for estimating damage and assessing global risk. This study evaluates the influence of barrier models compared to classical stationary models in analyzing the incidence of natural disasters in complex spatial regions, and demonstrates that the barrier model performs better in assessing spatial variance while maintaining the same computational cost.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Mathematics
Zongyuan Xia, Bo Tang, Long Qin, Huiguo Zhang, Xijian Hu
Summary: This study proposes a novel Bayesian spatial model that accurately estimates spatial effects in geostatistical data, and its effectiveness is validated through the practical application of tuberculosis incidence data.
Article
Health Care Sciences & Services
T. Baghfalaki, M. Ganjali
Summary: The study utilized the INLA approach for joint modeling of zero-inflated count and time-to-event data, introducing zero-inflated hurdle and Weibull models as sub-models, as well as a joint partially linear model. The method's performance was assessed through simulation studies and compared with MCMC approach, and applied to analyze two real datasets on pregnancy and HIV research.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2021)
Article
Geosciences, Multidisciplinary
Soraia Pereira, K. F. Turkman, Luis Correia, Havard Rue
Summary: This paper discusses the practice of geo-referencing sampling units and using point referenced models for unemployment estimation in the Portuguese Labour Force Survey. By modeling the spatial distribution of residential buildings using a log Gaussian Cox process, the study proposes a new method for estimating unemployment figures with higher spatial resolutions.
SPATIAL STATISTICS
(2021)
Article
Statistics & Probability
Samira Zahmatkesh, Mohsen Mohammadzadeh
Summary: This paper discusses methods for considering missing values in spatial data and proposes a joint spatial Bayesian shared parameter model. By modeling the missing process and measurement process together, using Bayesian inference for analysis, and conducting a simulation study on lake surface water temperature data, the efficiency of the spatial joint model is confirmed.
STATISTICAL PAPERS
(2021)
Article
Statistics & Probability
Somnath Chaudhuri, Pablo Juan, Jorge Mateu
Summary: Using accident records in an urban environment, this study develops a spatio-temporal model to predict the number of traffic collisions and generate risk maps for the entire road network. The use of SPDE network triangulation to estimate spatial autocorrelation on a linear network is a novel approach. The resulting risk maps offer valuable information for accident prevention and interdisciplinary road safety measures.
JOURNAL OF APPLIED STATISTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Marc Saez, Maria A. Barcelo
Summary: The objective of this study was to propose a hierarchical Bayesian spatiotemporal model for effective prediction of air pollution levels at low computational costs. By using the stochastic partial differential equations of the integrated nested Laplace approximations approximation, our model successfully predicted the levels of four pollutants with the most evidence of adverse health effects in Catalonia, Spain. Our model allowed accurate spatial predictions of both long-term and short-term exposure with a low density of monitoring stations and reduced computation time.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Chemistry, Multidisciplinary
Nora C. Monsalve, Antonio Lopez-Quilez
Summary: This paper proposes a structured additive regression (STAR) model for modeling the occurrence of a disease in fields or nurseries. The model utilizes Bayesian kriging to build prediction probability maps, providing computational efficiency and accuracy. The use of the integrated nested Laplace approximation (INLA) with the stochastic partial differential equation (SPDE) approach allows for efficient computation with large datasets. The methodology also allows for evaluation of different sampling strategies and recognition of spatial components' relevance in the studied phenomenon.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Zhi Li, Lei Liu, Jiaqiang Wang, Li Lin, Jichang Dong, Zhi Dong
Summary: In this paper, a Multi-Barriers Model is proposed to characterize an area of interest with different types of obstacles. The proposed model divides the area into sub-areas, one with sampling points and the other with obstacles. The correlation between points is determined by the obstruction degree of the obstacles, and stochastic partial differential equations are used to express continuous Gaussian fields. The model is verified using geostatistical and log-Gaussian Cox models, and its performance is compared with other models using real burglary data. The Multi-Barriers Model is found to better interpret spatial models with multiple obstacles and is closer to reality.
Article
Ecology
Jeffrey W. Doser, Andrew O. Finley, Sudipto Banerjee
Summary: Determining the spatial distributions of species and communities is important in ecology and conservation efforts. We developed a spatial factor multi-species occupancy model to explicitly account for species correlations, imperfect detection, and spatial autocorrelation. Ignoring these complexities leads to inferior model predictive performance, and our proposed model had the highest predictive performance among the alternative models.
Article
Psychology, Multidisciplinary
Yingying Han, Wenhao Pan, Jinjin Li, Ting Zhang, Qiang Zhang, Emily Zhang
Summary: During the COVID-19 pandemic, the subjective well-being (SWB) of Sina Weibo users showed a downward and then an upward trend. There was a significant correlation between the initial state and the development rate of SWB after the outbreak. The study identified two heterogeneous classes of SWB after the COVID-19 outbreak, with the higher growth group showing stronger adaptability to changes in their living environments.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Environmental Sciences
Guido Fioravanti, Michela Cameletti, Sara Martino, Giorgio Cattani, Enrico Pisoni
Summary: This study focuses on the relative changes in nitrogen dioxide (NO2) concentrations in northern Italy during the lockdown measures in March and April 2020. It is found that most of the studied area experienced negative changes, except for the first week of March and the fourth week of April. These changes cannot be attributed to weather factors and are likely a result of the lockdown measures. The study provides a unique statistical perspective and continuous maps of the spatial pattern of the NO2 relative changes.
Article
Ecology
Insa Thiermann, Daniel Schroer, Uwe Latacz-Lohmann
Summary: Recent legal changes have increased pressure on the German livestock industry to adapt. This study aims to identify the factors influencing German pig farmers' willingness to participate in an exit scheme similar to the Dutch 'warm restructuring' program. The analysis includes a discrete choice experiment conducted with 346 pig farmers. The results indicate a strong interest among respondents in a government-run decommissioning scheme. Differences in perceived scheme attributes, such as offered compensation, demolition requirements, and restrictions on future barn construction and slurry intake, are highlighted through latent-class estimation.
ECOLOGICAL ECONOMICS
(2023)
Article
Fisheries
Raul Vilela, Jose Maria Bellido
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
(2015)
Article
Fisheries
Caterina Dimitriadis, Ana Ines Borthagaray, Raul Vilela, Margarida Casadevall, Alvar Carranza
FISHERIES RESEARCH
(2016)
Article
Environmental Sciences
Raul Vilela, Ursula Pena, Ruth Esteban, Robin Koemans
MARINE POLLUTION BULLETIN
(2016)
Article
Fisheries
Maria Grazia Pennino, Raul Vilela, Jose M. Bellido, Francisco Velasco
FISHERIES OCEANOGRAPHY
(2019)
Article
Geosciences, Multidisciplinary
Maria Grazia Pennino, Raul Vilela, Jose M. Bellido
JOURNAL OF MARINE SYSTEMS
(2019)
Article
Fisheries
Maria Grazia Pennino, Elena Guijarro-Garcia, Raul Vilela, Jose Luis del Rio, Jose Maria Bellido
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
(2019)
Article
Multidisciplinary Sciences
Floriane Cardiec, Sophie Bertrand, Matthew J. Witt, Kristian Metcalfe, Brendan J. Godley, Catherine McClellan, Raul Vilela, Richard J. Parnell, Francois le Loc'h
Article
Environmental Sciences
Karin Hartman, Pieter van der Harst, Raul Vilela
FRONTIERS IN MARINE SCIENCE
(2020)
Article
Green & Sustainable Science & Technology
Gonzalo Rodriguez-Rodriguez, Hugo M. Ballesteros, Helena Martinez-Cabrera, Raul Vilela, Maria Grazia Pennino, Jose Maria Bellido
Summary: Natural resources management involves complex socioecological systems, requiring integration of different types of knowledge. This paper discusses the importance of diversity in knowledge types for interactive learning and innovation, using the Landing Obligation in Europe as a case study.
Article
Environmental Studies
Raul Vilela, Maria Grazia Pennino, Gonzalo Rodriguez-Rodriguez, Hugo M. Ballesteros, Jose Maria Bellido
Summary: The current EU discard ban has had implications for fishermen in terms of income and working time, with difficulties in implementation in mixed fisheries. A bio-economic model was constructed to analyze potential scenarios, showing that fishing ground selection is crucial for maximizing profits despite other measures such as fuel efficiency and crew size adjustments. Business-as-usual fishing strategies are likely to persist unless economic or regulatory pressures force changes.
Article
Environmental Studies
Esther Abad, Maria Grazia Pennino, Julio Valeiras, Raul Vilela, Jose Maria Bellido, Antonio Punzon, Francisco Velasco
Article
Environmental Studies
R. Vilela, D. Conesa, J. L. del Rio, A. Lopez-Quilez, J. Portela, J. M. Bellido
Article
Biodiversity Conservation
Paolo Casale, Gaspard Abitsi, Marie Pierre Aboro, Pierre Didier Agamboue, Laureen Agbode, Nontse Lois Allela, Davy Angueko, Jean Noel Bibang Bi Nguema, Francois Boussamba, Floriane Cardiec, Emmanuel Chartrain, Claudio Ciofi, Yves Armand Emane, J. Michael Fay, Brendan J. Godley, Carmen Karen Kouerey Oliwiwina, Jean de Dieu Lewembe, Donatien Leyoko, Georges Mba Asseko, Pulcherie Mengue M'adzaba, Jean Herve Mve Beh, Chiara Natali, Clauvice Nyama-Mouketou, Jacob Nzegoue, Carole Ogandagas, Richard J. Parnell, Guy Anicet Rerambyath, Micheline Schummer Gnandji, Guy-Philippe Sounguet, Manjula Tiwari, Bas Verhage, Raul Vilela, Lee White, Matthew J. Witt, Angela Formia
BIODIVERSITY AND CONSERVATION
(2017)