# Multivariate Spatio-Temporal Models using Structural Equations

## Documentation for package ‘tinyVAST’ version 1.3.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_mesh_covariates | Add mesh covariates to vertices and triangles
add_predictions | Add predictions to data-list
alaska_sponge_coral_fish | Data to analyze sponge-coral-fish associations
bering_sea | Survey domain for the eastern and northern Bering Sea surveys
bering_sea_capelin_forecasts | Data to demonstrate probabilistic forecasting
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
cAIC | Calculate conditional AIC
classify_variables | Classify variables path
conditional_gmrf | Conditional simulation from a GMRF
condition_and_density | Condition and density example
delta_gamma | Additional families
delta_lognormal | Additional families
deviance_explained | Calculate deviance explained
Families | Additional families
GetResponse.tinyVAST | Get response
get_data.tinyVAST | Get data
integrate_output | Integration for target variable
logLik.tinyVAST | Extract the (marginal) log-likelihood of a tinyVAST model
make_dsem_ram | Make a RAM (Reticular Action Model)
make_eof_ram | Make a RAM (Reticular Action Model)
make_sem_ram | Make a RAM (Reticular Action Model) from a SEM (structural equation model)
parse_path | Parse path
predict.tinyVAST | Predict using vector autoregressive spatio-temporal model
print.tinyVAST | print summary of tinyVAST model
project | Project tinyVAST to future times (EXPERIMENTAL)
red_grouper_diet | Data to demonstrate model-based diet proportions
red_snapper | Presence/absence, count, and biomass data for red snapper
red_snapper_shapefile | Shapefile for red snapper analysis
reload_model | Reload a previously fitted model
residuals.tinyVAST | Calculate deviance or response residuals for tinyVAST
rmvnorm_prec | Multivariate Normal Random Deviates using Sparse Precision
rotate_pca | Rotate factors to match Principal-Components Analysis
salmon_returns | North Pacific salmon returns
sample_variable | Sample from predictive distribution of a variable
sea_ice | Arctic September sea ice concentrations
sfnetwork_evaluator | Construct projection matrix for stream network
sfnetwork_mesh | Make mesh for stream network
simulate.tinyVAST | Simulate new data from a fitted model
simulate_sfnetwork | Simulate GMRF for stream network
spatial_cor | Approximate spatial correlation
summary.tinyVAST | summarize tinyVAST
term_covariance | Extract covariance
tinyVAST | Fit vector autoregressive spatio-temporal model
tinyVASTcontrol | Control parameters for tinyVAST
vcov.tinyVAST | Extract Variance-Covariance Matrix