Package index • sdmTMB

Mesh construction

Tools for converting coordinates into UTMs, constructing SPDE meshes prior to model fitting, and adding correlation barriers.

add_utm_columns() get_crs(): Add UTM coordinates to a data frame
make_mesh() plot(<sdmTMBmesh>): Construct an SPDE mesh for sdmTMB
add_barrier_mesh(): Transform a mesh object into a mesh with correlation barriers

Core tools for model fitting, prediction, and inspection.

sdmTMB(): Fit a spatial or spatiotemporal GLMM with TMB
sanity(): Sanity check of an sdmTMB model
tidy(<sdmTMB>) tidy(<sdmTMB_cv>): Turn sdmTMB model output into a tidy data frame
predict(<sdmTMB>): Predict from an sdmTMB model
residuals(<sdmTMB>): Residuals method for sdmTMB models
update(<sdmTMB>): Update an sdmTMB model
dharma_residuals(): DHARMa residuals
sdmTMBcontrol(): Optimization control options
run_extra_optimization() experimental: Run extra optimization on an already fitted object
replicate_df(): Replicate a prediction data frame over time
set_delta_model(): Set delta model for ggeffects::ggpredict()
make_category_svc(): Set up spatially varying coefficients for category composition models
coef(<sdmTMB>): Get fixed-effect coefficients
sigma(<sdmTMB>): Extract residual standard deviation or dispersion parameter
cAIC(): Calculate conditional AIC

Additional families beyond the standard R families.

Beta() lognormal() gengamma() gamma_mix() lognormal_mix() nbinom2_mix() nbinom2() nbinom1() truncated_nbinom2() truncated_nbinom1() student() tweedie() censored_poisson() delta_gamma() delta_gamma_mix() delta_gengamma() delta_lognormal() delta_lognormal_mix() delta_truncated_nbinom2() delta_truncated_nbinom1() delta_poisson_link_gamma() delta_poisson_link_lognormal() betabinomial() delta_beta(): Additional families

Optional priors or penalties on parameters.

sdmTMBpriors() normal() halfnormal() gamma_cv() mvnormal() pc_matern() experimental: Prior distributions
plot_pc_matern(): Plot PC Matérn priors

Simulating new data with an sdmTMB model.

Functions for plotting.

plot_anisotropy() plot_anisotropy2(): Plot anisotropy from an sdmTMB model
plot_smooth(): Plot a smooth term from an sdmTMB model
plot_pc_matern(): Plot PC Matérn priors
visreg_delta() visreg2d_delta(): Plot sdmTMB models with the visreg package

Functions related to cross validation.

sdmTMB_cv(): Cross validation with sdmTMB models
sdmTMB_stacking() experimental: Perform stacking with log scores on sdmTMB_cv() output
cv_to_waywiser() experimental: Convert sdmTMB_cv() objects to sf format for spatial assessment with waywiser

Derived quantities that can be calculated from sdmTMB models.

get_index() get_index_split() get_cog() get_weighted_average() get_eao(): Extract a relative biomass/abundance index, center of gravity, effective area occupied, or weighted average
get_index_sims() experimental: Calculate a population index via simulation from the joint precision matrix
get_range_edge() experimental: Calculate range edges via simulation from the joint precision matrix

Functions for calculating effect sizes or extracting parameter samples.

Effect.sdmTMB(): Calculate effects
emmeans.sdmTMB: Estimated marginal means with the emmeans package with sdmTMB
spread_sims() gather_sims(): Extract parameter simulations from the joint precision matrix