Package: tinyVAST 1.6.1

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. (2025) <doi:10.1111/geb.70035> for more details.

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

tinyVAST_1.6.1.tar.gz
tinyVAST_1.6.1.zip(r-4.7)tinyVAST_1.6.1.zip(r-4.6)tinyVAST_1.6.1.zip(r-4.5)
tinyVAST_1.6.1.tgz(r-4.6-x86_64)tinyVAST_1.6.1.tgz(r-4.6-arm64)tinyVAST_1.6.1.tgz(r-4.5-x86_64)tinyVAST_1.6.1.tgz(r-4.5-arm64)
tinyVAST_1.6.1.tar.gz(r-4.7-arm64)tinyVAST_1.6.1.tar.gz(r-4.7-x86_64)tinyVAST_1.6.1.tar.gz(r-4.6-arm64)tinyVAST_1.6.1.tar.gz(r-4.6-x86_64)
tinyVAST_1.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tinyVAST/json (API)

# 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/docs site:https://vast-lib.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

dynamic-structural-equation-modelsvector-autoregressive-spatio-temporal-modelcpp

7.93 score 17 stars 83 scripts 601 downloads 30 exports 136 dependencies

Last updated from:3fe4dd5934. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK433
linux-devel-x86_64OK489
source / vignettesOK630
linux-release-arm64OK433
linux-release-x86_64OK482
macos-release-arm64OK322
macos-release-x86_64OK697
macos-oldrel-arm64OK405
macos-oldrel-x86_64OK801
windows-develOK447
windows-releaseOK436
windows-oldrelOK428
wasm-releaseOK287

Exports:add_mesh_covariatesadd_predictionscAICconditional_gmrfdelta_gammadelta_lognormaldeviance_explainedintegrate_outputlognormalmake_dsem_rammake_eof_rammake_nngp_domainmake_sem_ramnbinom1nbinom2projectreload_modelrmvnorm_precrotate_pcasample_variablesanitysfnetwork_evaluatorsfnetwork_meshsimulate_sfnetworkspatial_corstudentterm_covariancetinyVASTtinyVASTcontroltweedie

Dependencies:abindassertthatbackportsbase64encBHbootbroomcachemcarcarDatacheckmateclassclassIntclicodetoolscolorspacecorpcorcowplotcpp11crayoncvDBIDerivdoBydoParalleldotCall64dplyrdseme1071farverfastmapfieldsfishModfmesherFNNforeachforecastFormulafracdiffgenericsgeometriesggforceggplot2ggraphggrepelglmmTMBglueGpGpGPvecchiagraphlayoutsgridExtragstatgtablegtoolsigraphinsightintervalsisobanditeratorsjsonliteKernSmoothlabelinglatticelifecyclelme4lmtestlwgeommagrittrmapsMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkminqamodelrmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolyclipproxypurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRTMBs2S7sandwichscalessdmTMBsfsfheaderssfnetworkssftimespspacetimespamsparseinvSparseMsplancsstarsstringistringrsurvivalsystemfontstibbletidygraphtidyrtidyselecttimeDateTMBtweenrunitsurcautf8vctrsviridisviridisLitewithrwkxtszoo

Dynamic structural equation models
Works cited
Rendered fromdsem.Rmdusingknitr::rmarkdown

Last update: 2026-05-19
Started: 2023-10-16

Multiple data types
Works cited
Rendered frommultiple_data.Rmdusingknitr::rmarkdown

Last update: 2025-12-21
Started: 2024-04-02

Spatial factor analysis
Works cited
Rendered fromspatial_factor_analysis.Rmdusingknitr::rmarkdown

Last update: 2025-12-21
Started: 2023-11-20

Comparison with mgcv
Rendered frommgcv.Rmdusingknitr::rmarkdown

Last update: 2025-09-15
Started: 2023-10-16

Spatial modeling
Percent deviance explained | Visualize spatial response
Rendered fromspatial.Rmdusingknitr::rmarkdown

Last update: 2025-09-15
Started: 2023-10-16

tinyVAST model description
Bivariate generalized linear mixed model structure | Spatial domains | Stochastic partial differentiaul equation (SPDE) | Simultaneous autoregressive (SAR): | Stream networks using a tail-down exponential correlation function | Structural equation models | Dynamic structural equation models | Spatial interactions for SEM and DSEM | Generalized additive model | Spatially varying coefficients | Notation summary | Works cited
Rendered frommodel-description.Rmdusingknitr::rmarkdown

Last update: 2025-07-19
Started: 2025-03-10

Readme and manuals

Help Manual

Help pageTopics
Add mesh covariates to vertices and trianglesadd_mesh_covariates
Add predictions to data-listadd_predictions
Data to analyze sponge-coral-fish associationsalaska_sponge_coral_fish
Northwest Atlantic yellowtailatlantic_yellowtail
Survey domain for the eastern and northern Bering Sea surveysbering_sea
Data to demonstrate probabilistic forecastingbering_sea_capelin_forecasts
Survey catch-rates at age for Alaska pollock in the Eastern and Northern Bering Seabering_sea_pollock_ages
Estimated proportion-at-age for Alaska pollock using VASTbering_sea_pollock_vast
Calculate conditional AICcAIC
Classify variables pathclassify_variables
Condition and density examplecondition_and_density
Conditional simulation from a GMRFconditional_gmrf
Calculate deviance explaineddeviance_explained
Additional familiesdelta_gamma delta_lognormal Families
Get dataget_data.tinyVAST
Get responseGetResponse.tinyVAST
Integration for target variableintegrate_output
Extract the (marginal) log-likelihood of a tinyVAST modellogLik.tinyVAST
Make a RAM (Reticular Action Model)make_dsem_ram
Make a RAM (Reticular Action Model)make_eof_ram
Make spatial object for NNGPmake_nngp_domain
Make a RAM (Reticular Action Model) from a SEM (structural equation model)make_sem_ram
Parse pathparse_path
Plot nngp_domainplot.nngp_domain
Predict using vector autoregressive spatio-temporal modelpredict.tinyVAST
print summary of tinyVAST modelprint.tinyVAST
Project tinyVAST to future times (EXPERIMENTAL)project
Data to demonstrate model-based diet proportionsred_grouper_diet
Presence/absence, count, and biomass data for red snapperred_snapper
Shapefile for red snapper analysisred_snapper_shapefile
Reload a previously fitted modelreload_model
Calculate deviance or response residuals for tinyVASTresiduals.tinyVAST
Multivariate Normal Random Deviates using Sparse Precisionrmvnorm_prec
Rotate factors to match Principal-Components Analysisrotate_pca
North Pacific salmon returnssalmon_returns
Sample from predictive distribution of a variablesample_variable
Sanity check of a tinyVAST modelsanity
Arctic September sea ice concentrationssea_ice
Construct projection matrix for stream networksfnetwork_evaluator
Make mesh for stream networksfnetwork_mesh
Simulate GMRF for stream networksimulate_sfnetwork
Simulate new data from a fitted modelsimulate.tinyVAST
Approximate spatial correlationspatial_cor
summarize tinyVASTsummary.tinyVAST
Extract covarianceterm_covariance
Fit vector autoregressive spatio-temporal modeltinyVAST
Control parameters for tinyVASTtinyVASTcontrol
Extract Variance-Covariance Matrixvcov.tinyVAST