Implements spatial and spatiotemporal predictive-process GLMMs (Generalized Linear Mixed Effect Models) using 'TMB', 'INLA', and the SPDE (Stochastic Partial Differential Equation) approximation to Gaussian random fields. One common application is for spatially explicit (and optionally dynamic) species distribution models (SDMs). See Anderson et al. (2022) <doi:10.1101/2022.03.24.485545>.
Version: | 0.3.0 |
Depends: | R (≥ 3.5.0) |
Imports: | assertthat, clisymbols, cli, fishMod, generics, glmmTMB, graphics, lifecycle, Matrix, methods, mgcv, mvtnorm, nlme, rlang, stats, TMB (≥ 1.8.0) |
LinkingTo: | RcppEigen, TMB |
Suggests: | dplyr, effects (≥ 4.0-1), estimability, emmeans (≥ 1.4), future, future.apply, ggeffects, ggforce, ggplot2, INLA, knitr, lme4, rgdal, rmarkdown, sf, splancs, testthat, tibble, visreg |
Published: | 2023-01-28 |
Author: | Sean C. Anderson |
Maintainer: | Sean C. Anderson <sean at seananderson.ca> |
BugReports: | https://github.com/pbs-assess/sdmTMB/issues |
License: | GPL-3 |
Copyright: | inst/COPYRIGHTS sdmTMB copyright details |
URL: | https://pbs-assess.github.io/sdmTMB/index.html, https://pbs-assess.github.io/sdmTMB/ |
NeedsCompilation: | yes |
SystemRequirements: | GNU make, C++17 |
Additional_repositories: | https://inla.r-inla-download.org/R/stable |
Citation: | sdmTMB citation info |
Materials: | NEWS |
In views: | SpatioTemporal |
CRAN checks: | sdmTMB results |
Reference manual: | sdmTMB.pdf |
Vignettes: |
sdmTMB model description |
Package source: | sdmTMB_0.3.0.tar.gz |
Windows binaries: | r-devel: sdmTMB_0.3.0.zip, r-release: sdmTMB_0.3.0.zip, r-oldrel: sdmTMB_0.3.0.zip |
macOS binaries: | r-release (arm64): sdmTMB_0.3.0.tgz, r-oldrel (arm64): sdmTMB_0.3.0.tgz, r-release (x86_64): sdmTMB_0.3.0.tgz, r-oldrel (x86_64): sdmTMB_0.3.0.tgz |
Old sources: | sdmTMB archive |
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