sdmTMB: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'

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:	0.2.1
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:	bayesplot, DHARMa, dplyr, effects (≥ 4.0-1), estimability, emmeans (≥ 1.4), future.apply, ggeffects, ggforce, ggplot2, INLA, knitr, rgdal, rmarkdown, rstan, sf, splancs, testthat, tibble, tmbstan, visreg
Published:	2023-01-10
Author:	Sean C. Anderson [aut, cre], Eric J. Ward [aut], Lewis A. K. Barnett [aut], Philina A. English [aut], James T. Thorson [ctb, cph] (VAST author), Joe Watson [ctb] (Censored Poisson), Julia Indivero [ctb] (Vignette writing), Cole C. Monnahan [ctb, cph] (VAST contributor), Mollie Brooks [ctb, cph] (glmmTMB author), Ben Bolker [ctb, cph] (glmmTMB author), Kasper Kristensen [ctb, cph] (TMB/glmmTMB author), Martin Maechler [ctb, cph] (glmmTMB author), Arni Magnusson [ctb, cph] (glmmTMB author), Hans J. Skaug [ctb, cph] (glmmTMB author, SPDE barrier), Anders Nielsen [ctb, cph] (glmmTMB author), Casper Berg [ctb, cph] (glmmTMB author), Koen van Bentham [ctb, cph] (glmmTMB author), Olav Nikolai Breivik [ctb, cph] (SPDE barrier), Simon Wood [ctb, cph] (mgcv: smoother prediction), Paul-Christian Bürkner [ctb, cph] (brms: smoother matrix parsing), His Majesty the King in Right of Canada, as represented by the Minister of the Department of Fisheries and Oceans [cph]
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++11
Additional_repositories:	https://inla.r-inla-download.org/R/stable
Citation:	sdmTMB citation info
Materials:	NEWS
CRAN checks:	sdmTMB results

Documentation:

Reference manual:

sdmTMB.pdf

Vignettes:

Intro to modelling with sdmTMB Bayesian estimation with sdmTMB Cross-validation for model evaluation and comparison Fitting delta (hurdle) models with sdmTMB Visualizing marginal effects in sdmTMB models with ggeffects Index standardization with sdmTMB sdmTMB model description Making pretty maps with sdmTMB output Residual checking with sdmTMB Fitting spatial trend models with sdmTMB Threshold modeling with sdmTMB Visualizing sdmTMB conditional effects using visreg

Downloads:

Package source:	sdmTMB_0.2.1.tar.gz
Windows binaries:	r-devel: sdmTMB_0.2.1.zip, r-release: sdmTMB_0.2.1.zip, r-oldrel: sdmTMB_0.2.1.zip
macOS binaries:	r-release (arm64): sdmTMB_0.2.1.tgz, r-oldrel (arm64): sdmTMB_0.2.1.tgz, r-release (x86_64): sdmTMB_0.2.1.tgz, r-oldrel (x86_64): sdmTMB_0.2.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=sdmTMB to link to this page.