bigDM

Scalable Bayesian disease mapping models (univariate and multivariate) for high-dimensional data using a divide and conquer approach.

The package
Installation
Basic Use
Updates
Copyright and license

The package

This package implements several (scalable) spatial and spatio-temporal Poisson mixed models for high-dimensional areal count data in a fully Bayesian setting using the integrated nested Laplace approximation (INLA) technique.

Below, there is a list with a brief overview of all package functions:

add_neighbour Adds isolated areas (polygons) to its nearest neighbour.
CAR_INLA Fits several spatial CAR models for high-dimensional count data.
clustering_partition Obtain a spatial partition using the DBSC algorithm.
connect_subgraphs Merges disjoint connected subgraphs.
divide_carto Divides the spatial domain into subregions.
grid_partition Defines a spatial partition of the spatial domain based on a regular grid.
kmeans_partition Define a random spatial partition of the domain based on k-means clustering of polygon centroids.
MCAR_INLA Fits several spatial multivariate CAR models for high-dimensional count data.
mergeINLA Merges inla objects for partition models.
Mmodel_compute_cor Computes between-disease correlation coefficients for M-models.
Mmodel_bym2 Implements the BYM2 multivariate latent effect.
Mmodel_idd Implements the spatially non-structured multivariate latent effect.
Mmodel_icar Implements the intrinsic multivariate latent effect.
Mmodel_lcar Implements the Leroux et al. (1999) multivariate latent effect.
Mmodel_pcar Implements the proper multivariate latent effect.
STCAR_INLA Fits several spatio-temporal CAR models for high-dimensional count data.

Installation

Installing Rtools45 for Windows

R version 4.6.0 and newer for Windows requires Rtools45 to build R packages with C/C++/Fortran code from source.

Install from CRAN

install.packages("bigDM")

Install from GitHub (development version)

# Install devtools package from CRAN repository
install.packages("devtools")

# Load devtools library
library(devtools)

# Install the R-INLA package
install.packages("INLA", repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)

# In some Linux OS, it might be necessary to first install the following packages
install.packages(c("cpp11","proxy","progress","tzdb","vroom"))

# Install bigDM from GitHub repositoy
install_github("spatialstatisticsupna/bigDM")

IMPORTANT NOTE: At least the stable version of INLA 22.11.22 (or newest) must be installed for the correct use of the bigDM package.

Basic Use

See the following vignettes for further details and examples using this package:

When using this package, please cite the following papers:

Orozco-Acosta, E., Adin, A., and Ugarte, M.D. (2021). Scalable Bayesian modeling for smoothing disease risks in large spatial data sets using INLA. Spatial Statistics, 41, 100496.

Orozco-Acosta, E., Adin, A., and Ugarte, M.D. (2023). Big problems in spatio-temporal disease mapping: methods and software. Computer Methods and Programs in Biomedicine, 231, 107403.

Vicente, G., Adin, A., Goicoa, T., and Ugarte, M.D. (2023). High-dimensional order-free multivariate spatial disease mapping. Statistics and Computing, 33, 104.

Updates

news(package="bigDM")

Changes in version 0.5.9 (2026 Oct 06)

BYM2 included as spatial prior for the MCAR_INLA() function
new kmeans_partition() function
random_partition() has been renamed to grid_partition()

Changes in version 0.5.8 (2026 Aug 19)

bugs fixed
package built for R-4.6

Changes in version 0.5.7 (2025 Sep 16)

support dummy-coded clusters as fixed effects in spatial and spatio-temporal models

Changes in version 0.5.6 (2025 Mar 25)

small changes for compatibility with the upcoming release of future
new 'scale.model' argument for CAR_INLA(), STCAR_INLA() and MCAR_INLA() functions
code adjustments

Changes in version 0.5.5 (2024 Aug 19)

condition for the upcoming release of tmap v4
small changes for compatibility with spdep version 1.3-6
new Data_MultiCancer object

Changes in version 0.5.4 (2024 May 30)

small bugs fixed and performance improvements
package built for R-4.4

Changes in version 0.5.3 (2023 Oct 17)

bugs fixed
faster implementation of divide_carto() function

Changes in version 0.5.2 (2023 Jun 14)

changes in mergeINLA() function
'X' argument included to STCAR_INLA() function

Changes in version 0.5.1 (2023 Feb 14)

small bugs fixed
new inla.mode and num.threads arguments for CAR_INLA(), STCAR_INLA() and MCAR_INLA() functions
adaptation of STCAR_INLA() function for spatio-temporal predictions
parallelization improvements using future package

Changes in version 0.5.0 (2022 Oct 27)

new MCAR_INLA() function to fit scalable spatial multivariate CAR models
changes in mergeINLA() function
development of additional auxiliary functions

Changes in version 0.4.2 (2022 Jun 27)

small bugs fixed
new merging strategy

Changes in version 0.4.1 (2022 Feb 01)

small bugs fixed
version submmited to CRAN

Changes in version 0.4.0 (2022 Jan 21)

new STCAR_INLA() function to fit scalable spatio-temporal CAR models

Changes in version 0.3.2 (2021 Nov 05)

X and confounding arguments included to CAR_INLA() function
new function included: clustering_partition()

Changes in version 0.3.1 (2021 May 03)

W argument included to CAR_INLA() function

Changes in version 0.3.0 (2021 Apr 19)

parallel and distributed computation strategies when fitting inla models with the CAR_INLA() function

Changes in version 0.2.2 (2021 Mar 12)

new arguments included to random_partition() function

Changes in version 0.2.1 (2021 Feb 25)

Carto_SpainMUN data changed

Changes in version 0.2.0 (2020 Oct 01)

speedup improvements in mergeINLA() function
small bugs fixed

Acknowledgments

This work has been supported by Project MTM2017-82553-R (AEI/FEDER, UE) and Project PID2020-113125RB-I00/MCIN/AEI/10.13039/501100011033. It has also been partially funded by the Public University of Navarra (project PJUPNA2001) and by la Caixa Foundation (ID 1000010434), Caja Navarra Foundation and UNED Pamplona, under agreement LCF/PR/PR15/51100007 (project REF P/13/20).

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