Package: tinyVAST 1.0.0

James T. Thorson

tinyVAST: Multivariate Spatio-Temporal Models using Structural Equations

Fits a wide variety of multivariate spatio-temporal models with simultaneous and lagged interactions among variables (including vector autoregressive spatio-temporal ('VAST') dynamics) for areal, continuous, or network spatial domains. It includes time-variable, space-variable, and space-time-variable interactions using dynamic structural equation models ('DSEM') as expressive interface, and the 'mgcv' package to specify splines via the formula interface. See Thorson et al. (2024) <doi:10.48550/arXiv.2401.10193> for more details.

Authors:James T. Thorson [aut, cre], Sean C. Anderson [aut]

tinyVAST_1.0.0.tar.gz
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tinyVAST.pdf |tinyVAST.html✨
tinyVAST/json (API)
NEWS

# Install 'tinyVAST' in R:

install.packages('tinyVAST', repos = c('https://vast-lib.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vast-lib/tinyvast/issues

Pkgdown site:https://vast-lib.github.io

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

bering_sea - Survey domain for the eastern and northern Bering Sea surveys
bering_sea_pollock_ages - Survey catch-rates at age for Alaska pollock in the Eastern and Northern Bering Sea
bering_sea_pollock_vast - Estimated proportion-at-age for Alaska pollock using VAST
condition_and_density - Condition and density example
red_snapper - Presence/absence, count, and biomass data for red snapper
red_snapper_shapefile - Shapefile for red snapper analysis
salmon_returns - North Pacific salmon returns
sea_ice - Arctic September sea ice concentrations

On CRAN:

vector-autoregressive-spatio-temporal-model cpp

6.80 score 13 stars 6 downloads 22 exports 67 dependencies

Last updated 8 hours agofrom:3ec5d4b30f. Checks:12 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 15 2025
R-4.5-win-x86_64	OK	Mar 15 2025
R-4.5-mac-x86_64	OK	Mar 15 2025
R-4.5-mac-aarch64	OK	Mar 15 2025
R-4.5-linux-x86_64	OK	Mar 15 2025
R-4.4-win-x86_64	OK	Mar 15 2025
R-4.4-mac-x86_64	OK	Mar 15 2025
R-4.4-mac-aarch64	OK	Mar 15 2025
R-4.4-linux-x86_64	OK	Mar 15 2025
R-4.3-win-x86_64	OK	Mar 15 2025
R-4.3-mac-x86_64	OK	Mar 15 2025
R-4.3-mac-aarch64	OK	Mar 15 2025

Exports:add_predictions cAIC delta_gamma delta_lognormal deviance_explained integrate_output lognormal make_dsem_ram make_eof_ram make_sem_ram nbinom1 nbinom2 reload_model rmvnorm_prec rotate_pca sample_variable sfnetwork_evaluator sfnetwork_mesh simulate_sfnetwork tinyVAST tinyVASTcontrol tweedie

Dependencies:abind arm assertthat backports boot checkmate class classInt cli clisymbols coda corpcor cpp11 crayon DBI dplyr e1071 fansi fishMod fmesher generics geometries glue igraph KernSmooth lattice lifecycle lme4 lwgeom magrittr MASS Matrix mgcv mi minqa mvtnorm nlme nloptr pillar pkgconfig proxy purrr R6 rbibutils Rcpp RcppEigen Rdpack reformulas rlang s2 sdmTMB sem sf sfheaders sfnetworks stringi stringr tibble tidygraph tidyr tidyselect TMB units utf8 vctrs withr wk

Comparison with mgcv

James T. Thorson

Rendered frommgcv.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2024-04-02
Started: 2023-10-16

Dynamic structural equation models

James T. Thorson

Rendered fromdsem.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2023-10-16

Multiple data types

James T. Thorson

Rendered frommultiple_data.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2024-04-02

Simultaneous autoregressive process

James T. Thorson

Rendered fromsimultaneous_autoregressive_process.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2023-12-04

Spatial factor analysis

James T. Thorson

Rendered fromspatial_factor_analysis.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2023-11-20

Spatial modeling

James T. Thorson

Rendered fromspatial.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2023-10-16

tinyVAST model description

James T. Thorson

Rendered frommodel-description.Rmdusingknitr::rmarkdownon Mar 15 2025.

Last update: 2025-03-10
Started: 2025-03-10

Help page	Topics
Add predictions to data-list	add_predictions
Survey domain for the eastern and northern Bering Sea surveys	bering_sea
Survey catch-rates at age for Alaska pollock in the Eastern and Northern Bering Sea	bering_sea_pollock_ages
Estimated proportion-at-age for Alaska pollock using VAST	bering_sea_pollock_vast
Calculate conditional AIC	cAIC
Classify variables path	classify_variables
Condition and density example	condition_and_density
Calculate deviance explained	deviance_explained
Additional families	delta_gamma delta_lognormal Families
Integration for target variable	integrate_output
Extract the (marginal) log-likelihood of a tinyVAST model	logLik.tinyVAST
Make a RAM (Reticular Action Model)	make_dsem_ram
Make a RAM (Reticular Action Model)	make_eof_ram
Make a RAM (Reticular Action Model) from a SEM (structural equation model)	make_sem_ram
Parse path	parse_path
Predict using vector autoregressive spatio-temporal model	predict.tinyVAST
print summary of tinyVAST model	print.tinyVAST
Presence/absence, count, and biomass data for red snapper	red_snapper
Shapefile for red snapper analysis	red_snapper_shapefile
Reload a previously fitted model	reload_model
Calculate deviance or response residuals for tinyVAST	residuals.tinyVAST
Multivariate Normal Random Deviates using Sparse Precision	rmvnorm_prec
Rotate factors to match Principal-Components Analysis	rotate_pca
North Pacific salmon returns	salmon_returns
Sample from predictive distribution of a variable	sample_variable
Arctic September sea ice concentrations	sea_ice
Construct projection matrix for stream network	sfnetwork_evaluator
Make mesh for stream network	sfnetwork_mesh
Simulate GMRF for stream network	simulate_sfnetwork
Simulate new data from a fitted model	simulate.tinyVAST
summarize tinyVAST	summary.tinyVAST
Fit vector autoregressive spatio-temporal model	tinyVAST
Control parameters for tinyVAST	tinyVASTcontrol
Extract Variance-Covariance Matrix	vcov.tinyVAST

Package: tinyVAST 1.0.0

tinyVAST: Multivariate Spatio-Temporal Models using Structural Equations

Comparison with mgcv

Dynamic structural equation models

Multiple data types

Simultaneous autoregressive process

Spatial factor analysis

Spatial modeling

tinyVAST model description

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)