bayestestR 0.18.1

Changes

• mcse() gains a centrality argument to return the appropriate MCSE.

Bug fixes

• Fixed failing CRAN checks.

bayestestR 0.18.0

New functionality

• Improved Bayes factor methods:

  • New docs at ?bayesfactor_methods

  • as.matrix() for bayesfactor_restricted(), to obtain a matrix of Bayes factors between all restricted models.

• Added support for CmdStanFit models from {cmdstanr} and expanded support for stanfit models from rstan.

Changes

• as.matrix(<bf>) now returns class bayesfactor_matrix and has a simpler printing.

• diagnostic_posterior() works with 'raw' MCMC samples (i.e., lists of data
  frames or matrices representing samples of parameters from chains, or 3D arrays)
  as well as objects from rstanarm/brms/lavaan models.

• diagnostic_posterior() now reports the tail-ESS (the minimum of the
  effective sample sizes for the 5% and 95% quantiles) in the ESS column,
  instead of the basic n_eff from older Stan versions. The tail-ESS is more
  relevant for assessing the reliability of credible intervals and other
  tail-based quantities. To also obtain the bulk-ESS (useful for central
  tendency estimates), pass "ESS_bulk" to the diagnostic argument.

• effective_sample() for stanfit objects now also returns the tail-ESS
  (ESS_tail), consistent with brmsfit and stanreg objects.

bayestestR 0.17.0

Changes

• rope() (and by extension p_rope()) gain a new complement argument such
  that rope(x, complement = TRUE) returns the ROPE posterior probability
  together with the posterior probabilities above/below the ROPE (the
  complementary probabilities).

• Added display() methods for bayestestR objects. The display() methods
  also get a new format option, format = "tt", to produce tables with the
  tinytable package.

• The long deprecated rnorm_perfect() function has been removed. Use
  distribution_normal() instead.

• Prepare for upcoming changes in marginaleffects (0.29.0).

bayestestR 0.16.1

Changes

• Improved efficiency for describe_posterior().

• Minor improvements for models with multinomial response variables.

• Minor improvements for mixture models from package brms.

bayestestR 0.16.0

Changes

• Revised code-base to address changes in latest insight update. Dealing with
  larger models (many parameters, many posterior samples) from packages brms
  and rstanarm is more efficient now. Furthermore, the options for the
  effects argument have a new behavior. "all" only returns fixed effects
  and random effects variance components, but no longer the group level
  estimates. Use effects = "full" to return all parameters. This change is
  mainly to be more flexible and gain more efficiency for models with many
  parameters and / or many posterior draws.

bayestestR 0.15.3

Changes

• effective_sample(), and functions that call effective_sample() (like
  describe_posterior() with the respective test option) now also return
  the tail ESS.

Bug fixes

• describe_posterior() now returns a columns with response levels for
  marginaleffects objects applied to categorical or multinomial Stan models.

• describe_posterior() now returns a columns with response variables for
  marginaleffects objects applied to multivariate response Stan models.

• Fixed issue in map_estimate() and point_estimate(centrality = "MAP") for
  vectors with only one unique value.

bayestestR 0.15.2

Changes

• describe_posterior() no longer re-samples a model when computing
  indices.

• describe_posterior() calls tests only when needed. Before, there was a
  minimal overhead by calling tests that were not requested.

Bug fixes

• Fixed failing test for Mac OS.

bayestestR 0.15.1

Changes

• Several minor changes to deal with recent changes in other packages.

Bug fixes

• Fix to emmeans / marginaleffects / data.frame(<rvar>) methods when using multiple credible levels (#688).

bayestestR 0.15.0

Changes

• Support for posterior::rvar-type column in data frames.
  For example, a data frame df with an rvar column ".pred" can now be
  called directly via p_direction(df, rvar_col = ".pred").

• Added support for {marginaleffects}

• The ROPE or threshold ranges in rope(), describe_posterior(), p_significance()
  and equivalence_test() can now be specified as a list. This allows for different
  ranges for different parameters.

• Results from objects generated by {emmeans} (emmGrid/emm_list) now
  return results with appended grid-data.

• Usability improvements for p_direction():

  • Results from p_direction() can directly be used in pd_to_p().

  • p_direction() gets an as_p argument, to directly convert pd-values into
    frequentist p-values.

  • p_direction() gets a remove_na argument, which defaults to TRUE, to
    remove NA values from the input before calculating the pd-values.

  • Besides the existing as.numeric() method, p_direction() now also has an
    as.vector() method.

• p_significance() now accepts non-symmetric ranges for the threshold argument.

• p_to_pd() now also works with data frames returned by p_direction(). If
  a data frame contains a pd, p_direction or PD column name, this is assumed
  to be the pd-values, which are then converted to p-values.

• p_to_pd() for data frame inputs gets a as.numeric() and as.vector()
  method.

Bug fixes

• Fixed warning in CRAN check results.

bayestestR 0.14.0

Breaking Changes

• Arguments named group, at, group_by and split_by will be deprecated
  in future releases of easystats packages. Please use by instead. This
  affects following functions in bayestestR:

  • estimate_density()

Changes

• bayesian_as_frequentist() now supports more model families from Bayesian
  models that can be successfully converted to their frequentists counterparts.

• bayesfactor_models() now throws an informative error when Bayes factors for
  comparisons could not be calculated.

Bug fixes

• Fixed issue in bayesian_as_frequentist() for brms models with 0 + Intercept
  specification in the model formula.