Applied Spatial Data Analysis in geoscience
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Updated
Feb 2, 2023 - R
Applied Spatial Data Analysis in geoscience
An R package for Bayesian structural equation modeling using INLA
Supplementary material and reproducible research files for article “A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations” by Emma Skarstein, Sara Martino and Stefanie Muff.
Models of the expansion of the black death and cholera outbreaks
This repository contains code to perform the wildlife density modelling approach outlined in Houldcroft et al. (2024).
A Shiny App for Spatial Modeling. It allows the users to perform geostatistical models, LGCP models, preferential models and joint models with mixture independent-dependent samplings (which we will refer as mixture models). This is done under the Bayesian paradigm and by means of the INLA approach.
This repository contains example code to estimate spatially smoothed small area estimates of firearm suicide mortality rates across counties in the contiguous United States.
Streamlined Model-based Geostatistics Functions for the SEEG Research Group
Predicting insecticide use across Canada
Online version of Dynamic Time Series Models using R-INLA: An Applied Perspective. Ravishanker, Raman, Soyer, 2022. Also includes R codes and data sets from the book.
Code in support of 'Bioclimatic context of species’ populations determines community stability' by Evans et al
Approximate inference of latent non-Gaussian models
R library for ggplots of INLA Fixed Effect Coefficients
This repository is out of date. See instead: https://github.com/paigejo/ELK
An R package with useful functions to diagnose INLA models
Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature
Elevational variation in tropical trees analysis
Temporal Integrative Genomics Analysis in R
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