Results 31 to 40 of about 15,041,214 (186)
, 2021 The statistical methods used to analyze medical data are becoming increasingly complex. Novel statistical methods increasingly rely on simulation studies to assess their validity. Such assessments typically appear in statistical or computational journals, and the methodology is later introduced to the medical community through tutorials.
Khan K, Luo H, Xi W.
europepmc +3 more sources
Modelación espacio-temporal de la incidencia acumulada de COVID-19 en municipios de Chiapas
ESPACIO I+D: Innovación más Desarrollo, 2020 El trabajo tiene como finalidad analizar la evolución de la tasa de incidencia acumulada de COVID-19 en los municipios de Chiapas, entre los meses de Febrero a Julio del año 2020, a partir de la aplicación de tres modelos bayesianos jerárquicos espacio ...
Gerardo Núñez Medina
doaj +1 more source
Numerical Recipes for Landslide Spatial Prediction Using R-INLA [PDF]
, 2019 The geomorphological community typically assesses the landslide susceptibility at the catchment or larger scales through spatial predictive models. However, the spatial information is conveyed only through the geographical distribution of the covariates.
Lombardo, Luigi +2 more
openaire +4 more sources
A joint Bayesian space–time model to integrate spatially misaligned air pollution data in R‐INLA [PDF]
Environmetrics, 2020 AbstractIn air pollution studies, dispersion models provide estimates of concentration at grid level covering the entire spatial domain and are then calibrated against measurements from monitoring stations. However, these different data sources are misaligned in space and time. If misalignment is not considered, it can bias the predictions.
C. Forlani +4 more
openaire +5 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
R script for fitting Bayesian spatiotemporal zero-inflated models using INLA
, 2023 This R code illustrates the steps of fitting Bayesian spatiotemporal zero-inflated models with INLA.
Hui Luan (14300165)
core +1 more source
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
INLAjoint: Multivariate Joint Modeling for Longitudinal and Time-to-Event Outcomes with 'INLA'
, 2023 Estimation of joint models for multivariate longitudinal markers (with various distributions available) and survival outcomes (possibly accounting for competing risks) with Integrated Nested Laplace Approximations (INLA).
Van Niekerk, Janet +3 more
core +1 more source
Spatial modelling of agro-ecologically significant grassland species using the INLA-SPDE approach [PDF]
, 2023 The use of spatially referenced data in agricultural systems modelling has grown in recent decades, however, the use of spatial modelling techniques in agricultural science is limited.
Fichera, Andrew +9 more
core +1 more source
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