Package: bigDM 0.5.5
bigDM: Scalable Bayesian Disease Mapping Models for High-Dimensional Data
Implements several spatial and spatio-temporal scalable disease mapping models for high-dimensional count data using the INLA technique for approximate Bayesian inference in latent Gaussian models (Orozco-Acosta et al., 2021 <doi:10.1016/j.spasta.2021.100496>; Orozco-Acosta et al., 2023 <doi:10.1016/j.cmpb.2023.107403> and Vicente et al., 2023 <doi:10.1007/s11222-023-10263-x>). The creation and develpment of this package 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).
Authors:
bigDM_0.5.5.tar.gz
bigDM_0.5.5.zip(r-4.5)bigDM_0.5.5.zip(r-4.4)bigDM_0.5.5.zip(r-4.3)
bigDM_0.5.5.tgz(r-4.4-any)bigDM_0.5.5.tgz(r-4.3-any)
bigDM_0.5.5.tar.gz(r-4.5-noble)bigDM_0.5.5.tar.gz(r-4.4-noble)
bigDM_0.5.5.tgz(r-4.4-emscripten)bigDM_0.5.5.tgz(r-4.3-emscripten)
bigDM.pdf |bigDM.html✨
bigDM/json (API)
NEWS
# Install 'bigDM' in R: |
install.packages('bigDM', repos = c('https://spatialstatisticsupna.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/spatialstatisticsupna/bigdm/issues
- Carto_SpainMUN - Spanish colorectal cancer mortality data
- Data_LungCancer - Spanish lung cancer mortality data
- Data_MultiCancer - Spanish cancer mortality data for the joint analysis of multiple diseases
Last updated 3 months agofrom:e42193e7a3. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 17 2024 |
R-4.5-win | OK | Nov 17 2024 |
R-4.5-linux | OK | Nov 17 2024 |
R-4.4-win | NOTE | Nov 17 2024 |
R-4.4-mac | NOTE | Nov 17 2024 |
R-4.3-win | NOTE | Nov 17 2024 |
R-4.3-mac | NOTE | Nov 17 2024 |
Exports:add_neighbourCAR_INLAclustering_partitionconnect_subgraphsdivide_cartoMCAR_INLAmergeINLAMmodel_compute_corMmodel_icarMmodel_iidMmodel_lcarMmodel_pcarrandom_partitionSTCAR_INLA
Dependencies:bootclassclassIntclicodacodetoolscrayondata.tableDBIdeldirdigestdoParallele1071fansifastDummiesforeachfuturefuture.applygeosglobalsglueiteratorsjsonliteKernSmoothlatticeLearnBayeslibgeoslifecyclelistenvmagrittrMASSMatrixmultcompmvtnormnlmeparallellypillarpkgconfigproxyrbibutilsRColorBrewerRcppRdpackrlangrlists2sandwichsfspspatialregspDataspdepstringistringrsurvivalTH.datatibbleunitsutf8vctrswkXMLyamlzoo