best_models() now
takes a character prior argument in place of the integer
criterion argument. Use prior = "binomial"
(default) instead of criterion = 1, and
prior = "beta" instead of criterion = 2. This
brings the API in line with summary.badp_bma(), which
already used prior = "binomial" | "beta".dil.Par
parameter to omega for clarity and consistency with
statistical literature.bma() now returns an object of class
badp_bma (previously unclassed list).optim_model_space() now returns an object of class
badp_model_space.badp_bma objects:
print.badp_bma() - Clean, informative console
output.summary.badp_bma() - Detailed statistical summary with
highlighted important variables. Enhanced to display BMA statistics for
both binomial and binomial-beta priors simultaneously.coef.badp_bma() - Extract coefficients with optional
standard errors and PIPs.plot.badp_bma() - Default visualization with dispatch
to existing plot functions.print.badp_model_space() for model space
objects.bma() output: removed spaces,
duplicates, and typos; all names are now valid R identifiers (e.g.,
uniform_table, random_table,
reg_names, dilution,
alphas).results[[3]]) and helper functions
(best_models(), jointness(), etc.) are fully
preserved. Named access is available via the new identifiers (e.g.,
results$reg_names), but code using the previous long
component names must be updated.@keywords internal to
hide helper and implementation functions from user-facing help
documentation.sem_likelihood example: use the bundled
economic_growth dataset instead of small random data that
could produce NA or invalid positive values on some
platforms.ggpubr dependency; plotting functions now use
patchwork for plot arrangement.migration_data dataset with migration flows data
from Afonso, Alves, & Beck (2025).migration_model_space and
migration_model_space_nonnested example model space
objects.feature_standardization function to handle tibble
input correctly.join_lagged_col function.n_ prefix for counts, df_free for
degrees of freedom).bdsm to badp
(Bayesian Averaging for Dynamic Panels).df argument from the bma
function; data is no longer required at the BMA stage.posterior_dens function for plotting posterior
densities of coefficients.coef_hist via
the weight parameter (based on posterior model
probabilities).extract_names function.optim_model_space.bma function for improved robustness and
compatibility.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.