portalcasting v0.51.0

Major updates to pkgdown site

• Shift to bootstrap 5

Include CI tests of \dontrun examples and eval=FALSE vignettes

• Because of the long run time of some of the code, we wrap most documentation examples and vignette code in a way to prevent evaluation in real-time. As a result, much of the documentation code isn't run and therefore would not break builds if it would error.
• To address this, we add two scripts in the new inst/extra_testing folder and a github action runner for each.

Added CITATION file

• Cites the JOSS paper.

Bringing the app code into the package

• Improves robustness of building the app (includes code and dependencies in the docker image, allows for unit testing app components, etc.)
• Also allows users to spin-up a local version with run_web_app() pointed to main

Using arrow to speed up reading and writing files

Evaluation figures now read from evaluations file

• Avoids computing evaluations while generating plots

Elimination of model-named functions

• The models are now implemented using cast on their fit and cast elements in their control lists
• Only models the need new functions have them (meta_tsglm and fit_runjags) for fitting
• forecast method used generally now for cast function
  • introduction of forecast methods for tsglm and runjags objects

Shifting covariates to a daily-level build initial step

• need to shift this to level daily so we can manage when a newmoon is split between historic and forecast days

Putting species under dataset in the models' controls lists

• This is more articulated and allows for finer control to help avoid fitting issues, etc.

Moving arguments into functionalities

• cast_date is not an argument anymore, just filled automatically
• dataset arguments are also being removed as possible to streamline (just pull from model controls)

Model functions are now species-level

• To facilitate a lot of downstream functionality, we're breaking up the model functions to operate on the species-level rather than the dataset-level, according to the new control lists
• Species that were failing the nb GARCH models (s or not) have been removed, since that throws a warning and then fits a Poisson version, and we are now fitting Poisson versions of everyone.

process_model_output replaces save_cast_output and various model processing bits

• provides a much more general way to produce a forecast that can be integrated in the system, leveraging the metadata files

casts metadata table includes new column

• species
• to facilitate backwards compatibility, filled with NA for previous tables if missing when loaded

updates to prefab models to 13 time steps forward (addressing issue 297)

• pevGARCH, nbGARCH, nbsGARCH all get past_mean set to 13
• all models set with lead_time of 13

new models

• sAutoArima
• sNaiveArima
• pGARCH
• psGARCH

new functions

• update_dir is an "update-flavored" setup function

scoring

• log and crps!