Scalable Bayesian Disease Mapping Models for High-Dimensional Data


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Documentation for package ‘bigDM’ version 0.4.2

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bigDM-package Scalable Bayesian Disease Mapping Models for High-Dimensional Data
add_neighbour Add isolated areas (polygons) to its nearest neighbour
bigDM Scalable Bayesian Disease Mapping Models for High-Dimensional Data
Carto_SpainMUN Spanish colorectal cancer mortality data
CAR_INLA Fit a (scalable) spatial Poisson mixed model to areal count data, where several CAR prior distributions can be specified for the spatial random effect.
clustering_partition Obtain a partition of the spatial domain using the density-based spatial clustering (DBSC) algorithm described in Santafé et al. (2021)
connect_subgraphs Merge disjoint connected subgraphs
Data_LungCancer Spanish lung cancer mortality data
divide_carto Divide the spatial domain into subregions
mergeINLA Merge 'inla' objects for partition models
random_partition Define a random partition of the spatial domain based on a regular grid
STCAR_INLA Fit a (scalable) spatio-temporal Poisson mixed model to areal count data.