Results 41 to 50 of about 5,509 (173)

A geostatistical model for combined analysis of point-level and area-level data using INLA and SPDEerri [PDF]

, 2017
\ud \ud In this paper a Bayesian geostatistical model is presented for fusion of data obtained at point and areal resolutions. The model is fitted using the INLA and SPDE approaches.
Moraga, Paula, Cramb, S., Marcello Pagano, Cramb, Susanna M., Mengersen, Kerrie L., Pagano, Marcello, Paula Moraga, Moraga, P., Susanna M. Cramb, Mengersen, K., Pagano, M., Kerrie L. Mengersen   +11 more
core   +2 more sources

Mapping and understanding the regional farmland SOC distribution in southern China using a Bayesian spatial model

Geoderma
Information on the spatial distribution of soil organic carbon (SOC) in regional farmland is crucial for improving management and production. Mapping SOC in farmlands is challenging due to the strong variation of SOC caused by the influence of natural ...
Bifeng Hu, Yibo Geng, Hanjie Ni, Zhou Shi, Zheng Wang, Nan Wang, Jipeng Luo, Modian Xie, Qian Zou, Thomas Optiz, Hongyi Li   +10 more
doaj   +1 more source

Spatiotemporal Distribution Patterns and Influencing Factors of Pulmonary Tuberculosis in Xinjiang: Based on Hierarchical Bayesian Model [PDF]

Zhongguo quanke yixue
Background China ranks third globally in tuberculosis burden and is classified as one of the highest tuberculosis (TB) burden countries. Xinjiang, a multi-ethnic region in northwestern China, has consistently reported one of the highest TB incidence ...
LI Feifei, ZHOU Peiyao, LU Yaoqin, ZHENG Yanling, ZHANG Liping
doaj   +1 more source

Field-scale digital soil mapping of clay: Combining different proximal sensed data and comparing various statistical models [PDF]

, 2020
Knowledge about clay fraction is important for soil management. Laboratory analysis is time consuming, however, because information is required at the topsoil (0‒0.3 m), subsurface (0.3‒0.6 m), and subsoil (0.9‒1.2 m).
Li, N, Bella, LD, Triantafilis, J ; https://orcid.org/, Arshad, M   +3 more
core   +1 more source

Approximate Bayesian inference based on INLA algorithm

Statistical Theory and Related Fields
The integrated nested Laplace approximation (INLA) algorithm provides a computationally efficient approach for approximate Bayesian inference, overcoming the limitations of traditional Markov chain Monte Carlo (MCMC) methods.
Pingping Wang, Wei Zhao, Yincai Tang
doaj   +1 more source

Pesticides and Hypospadias in Southern Brazil: An Ecological Study

Environmental Toxicology, EarlyView.
ABSTRACT Rio Grande do Sul ranks among the Brazilian states with the highest pesticide consumption and one of the highest prevalences of hypospadias, a congenital anomaly often associated with prenatal exposure to endocrine‐disrupting chemicals. We assessed the relationship between prenatal pesticide exposure and hypospadias risk through an ecological ...
Ricardo Rohweder, Márcia Barbian, Juliana da Silva, Nadia Spada Fiori, Lavinia Schuler‐Faccini   +4 more
wiley   +1 more source

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

International Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula Moraga   +2 more
wiley   +1 more source

Assessing the risk of extreme precipitation in Japan through GEV distribution and spatial modeling

Journal of Hydrology: Regional Studies
Study region: Japan, characterized by diverse climatic zones and complex topography, has experienced increasing frequency and severity of extreme precipitation events in recent decades.
Zhichao Jiao, Jihui Yuan, Craig Farnham, Kazuo Emura   +3 more
doaj   +1 more source

Bayesian Hierarchical Models for the Combination of Spatially Misaligned Data: A Comparison of Melding and Downscaler Approaches Using INLA and SPDE

, 2023
The spatially misaligned data problem occurs when data at different spatial scales need to be combined. Bayesian hierarchical models such as melding and downscaler approaches are suitable to solve this problem but their application is limited when MCMC ...
Ruiman Zhong, Moraga, Paula, Zhong, Ruiman, Paula Moraga   +3 more
core   +1 more source

sdmTMB: An R Package for Fast, Flexible, and User-Friendly Generalized Linear Mixed Effects Models with Spatial and Spatiotemporal Random Fields

Journal of Statistical Software
Geostatistical spatial or spatiotemporal data are common across scientific fields. However, appropriate models to analyze these data, such as generalized linear mixed effects models (GLMMs) with Gaussian Markov random fields (GMRFs), are computationally ...
Sean C. Anderson, Eric J. Ward, Philina A. English, Lewis A. K. Barnett, James T. Thorson   +4 more
doaj   +1 more source