NEWS
mvgam 1.1.3 (2024-09-04)
New functionalities
- Allow intercepts to be included in process models when
trend_formula
is supplied. This breaks the assumption that the process has to be zero-centred, adding more modelling flexibility but also potentially inducing nonidentifiabilities with respect to any observation model intercepts. Thoughtful priors are a must for these models
- Added
standata.mvgam_prefit
, stancode.mvgam
and stancode.mvgam_prefit
methods for better alignment with 'brms' workflows
- Added 'gratia' to Enhancements to allow popular methods such as
draw()
to be used for 'mvgam' models if 'gratia' is already installed
- Added an
ensemble.mvgam_forecast
method to generate evenly weighted combinations of probabilistic forecast distributions
- Added an
irf.mvgam
method to compute Generalized and Orthogonalized Impulse Response Functions (IRFs) from models fit with Vector Autoregressive dynamics
Deprecations
- The
drift
argument has been deprecated. It is now recommended for users to include parametric fixed effects of "time" in their respective GAM formulae to capture any expected drift effects
Bug fixes
- Added a new check to ensure that exception messages are only suppressed by the
silent
argument if the user's version of 'cmdstanr' is adequate
- Updated dependency for 'brms' to version >= '2.21.0' so that
read_csv_as_stanfit
can be imported, which should future-proof the conversion of 'cmdstanr' models to stanfit
objects (#70)
mvgam 1.1.2 (2024-07-01)
New functionalities
- Added options for silencing some of the 'Stan' compiler and modeling messages using the
silent
argument in mvgam()
- Moved a number of packages from 'Depends' to 'Imports' for simpler package loading and fewer potential masking conflicts
- Improved efficiency of the model initialisation by tweaking parameters of the underlying 'mgcv'
gam
object's convergence criteria, resulting in much faster model setups
- Added an option to use
trend_model = 'None'
in State-Space models, increasing flexibility by ensuring the process error evolves as white noise (#51)
- Added an option to use the non-centred parameterisation for some autoregressive trend models,
which speeds up mixing most of the time
- Updated support for multithreading so that all observation families (apart from
nmix()
) can now be modeled with multiple threads
- Changed default priors on autoregressive coefficients (AR1, AR2, AR3) to enforce
stationarity, which is a much more sensible prior in the majority of contexts
Bug fixes
- Fixed a small bug that prevented
conditional_effects.mvgam()
from handling effects with three-way interactions
mvgam 1.1.1 (2024-05-10)
New functionalities
- Changed indexing of an internal c++ function after Prof Brian Ripley’s
email: Dear maintainer, Please see the problems shown on
https://cran.r-project.org/web/checks/check_results_mvgam.html. Please correct before 2024-05-22 to safely retain your package on CRAN. The CRAN Team
mvgam 1.1.0 (2024-05-06)
- First release of
mvgam
to CRAN