Changes in version 0.18.1 (2026-05-24)                 

Changes

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

Bug fixes

  - Fixed failing CRAN checks.

                 Changes in version 0.18.0 (2026-05-21)                 

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.

                 Changes in version 0.17.0 (2025-08-29)                 

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).

                 Changes in version 0.16.1 (2025-07-01)                 

Changes

  - Improved efficiency for describe_posterior().

  - Minor improvements for models with multinomial response variables.

  - Minor improvements for mixture models from package brms.

                 Changes in version 0.16.0 (2025-05-20)                 

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.

                 Changes in version 0.15.3 (2025-04-28)                 

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.

                 Changes in version 0.15.2 (2025-02-07)                 

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.

                 Changes in version 0.15.1 (2025-01-17)                 

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).

                 Changes in version 0.15.0 (2024-10-17)                 

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.

                 Changes in version 0.14.0 (2024-07-24)                 

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.

                 Changes in version 0.13.2 (2024-02-12)                 

Breaking Changes

  - pd_to_p() now returns 1 and a warning for values smaller than 0.5.

  - map_estimate(), p_direction(), p_map(), and p_significance() now
    return a data-frame when the input is a numeric vector. (making the
    output consistently a data frame for all inputs.)

  - Argument posteriors was renamed into posterior. Before, there were a
    mix of both spellings, now it is consistently posterior.

Changes

  - Retrieving models from the environment was improved.

Bug fixes

  - Fixed issues in various format() methods, which did not work
    properly for some few functions (like p_direction()).

  - Fixed issue in estimate_density() for double vectors that also had
    other class attributes.

  - Fixed several minor issues and tests.

                 Changes in version 0.13.1 (2023-04-07)                 

Changes

  - Improved speed performance when functions are called using
    do.call().

  - Improved speed performance to bayesfactor_models() for brmsfit
    objects that already included a marglik element in the model object.

New functionality

  - as.logical() for bayesfactor_restricted() results, extracts the
    boolean vector(s) the mark which draws are part of the order
    restriction.

Bug fixes

  - p_map() gains a new null argument to specify any non-0 nulls.

  - Fixed non-working examples for ci(method = "SI").

  - Fixed wrong calculation of rope range for model objects in
    describe_posterior().

  - Some smaller bug fixes.

                 Changes in version 0.13.0 (2022-09-18)                 

Breaking

  - The minimum needed R version has been bumped to 3.6.

  - contr.equalprior(contrasts = FALSE) (previously contr.orthonorm) no
    longer returns an identity matrix, but a shifted diag(n) - 1/n, for
    consistency.

New functionality

  - p_to_bf(), to convert p-values into Bayes factors. For more accurate
    approximate Bayes factors, use bic_to_bf().
  - bayestestR now supports objects of class rvar from package
    posterior.
  - contr.equalprior (previously contr.orthonorm) gains two new
    functions: contr.equalprior_pairs and contr.equalprior_deviations to
    aide in setting more intuitive priors.

Changes

  - has been renamed contr.equalprior to be more explicit about its
    function.
  - p_direction() now accepts objects of class parameters_model() (from
    parameters::model_parameters()), to compute probability of direction
    for parameters of frequentist models.

                 Changes in version 0.12.1 (2022-05-02)                 

Breaking

  - Bayesfactor_models() for frequentist models now relies on the
    updated insight::get_loglikelihood(). This might change some results
    for REML based models. See documentation.

  - estimate_density() argument group_by is renamed at.

  - All distribution_*(random = FALSE) functions now rely on ppoints(),
    which will result in slightly different results, especially with
    small ns.

  - Uncertainty estimation now defaults to "eti" (formerly was "hdi").

Changes

  - bayestestR functions now support draws objects from package
    posterior.

  - rope_range() now handles log(normal)-families and models with
    log-transformed outcomes.

  - New function spi(), to compute shortest probability intervals.
    Furthermore, the "spi" option was added as new method to compute
    uncertainty intervals.

Bug fixes

  - bci() for some objects incorrectly returned the equal-tailed
    intervals.

                 Changes in version 0.11.5 (2021-10-30)                 

  - Fixes failing tests in CRAN checks.

                       Changes in version 0.11.1                        

New functions

  - describe_posterior() gains a plot() method, which is a short cut for
    plot(estimate_density(describe_posterior())).

                        Changes in version 0.11                         

Bug fixes

  - Fixed issues related to last brms update.

  - Fixed bug in describe_posterior.BFBayesFactor() where Bayes factors
    were missing from out put ( #442 ).

                 Changes in version 0.10.0 (2021-05-31)                 

Breaking

  - All Bayes factors are now returned as log(BF) (column name log_BF).
    Printing is unaffected. To retrieve the raw BFs, you can run
    exp(result$log_BF).

New functions

  - bci() (and its alias bcai()) to compute bias-corrected and
    accelerated bootstrap intervals. Along with this new function, ci()
    and describe_posterior() gain a new ci_method type, "bci".

Changes

  - contr.bayes has been renamed contr.orthonorm to be more explicit
    about its function.

                 Changes in version 0.9.0 (2021-04-08)                  

Breaking

  - The default ci width has been changed to 0.95 instead of 0.89 (see
    here). This should not come as a surprise to the long-time users of
    bayestestR as we have been warning about this impending change for a
    while now :)

  - Column names for bayesfactor_restricted() are now p_prior and
    p_posterior (was Prior_prob and Posterior_prob), to be consistent
    with bayesfactor_inclusion() output.

  - Removed the experimental function mhdior.

General

  - Support for blavaan models.

  - Support for blrm models (rmsb).

  - Support for BGGM models (BGGM).

  - check_prior() and describe_prior() should now also work for more
    ways of prior definition in models from rstanarm or brms.

Bug fixes

  - Fixed bug in print() method for the mediation() function.

  - Fixed remaining inconsistencies with CI values, which were not
    reported as fraction for rope().

  - Fixed issues with special prior definitions in check_prior(),
    describe_prior() and simulate_prior().

                 Changes in version 0.8.2 (2021-01-26)                  

General

  - Support for bamlss models.

  - Roll-back R dependency to R >= 3.4.

Changes to functions

  - All .stanreg methods gain a component argument, to also include
    auxiliary parameters.

Bug fixes

  - bayesfactor_parameters() no longer errors for no reason when
    computing extremely un/likely direction hypotheses.

  - bayesfactor_pointull() / bf_pointull() are now
    bayesfactor_pointnull() / bf_pointnull() (can you spot the
    difference? #363 ).

                 Changes in version 0.8.0 (2020-12-05)                  

New functions

  - sexit(), a function for sequential effect existence and significance
    testing (SEXIT).

General

  - Added startup-message to warn users that default ci-width might
    change in a future update.

  - Added support for mcmc.list objects.

Bug fixes

  - unupdate() gains a newdata argument to work with brmsfit_multiple
    models.

  - Fixed issue in Bayes factor vignette (don't evaluate code chunks if
    packages not available).

                 Changes in version 0.7.5 (2020-10-22)                  

New functions

  - Added as.matrix() function for bayesfactor_model arrays.

  - unupdate(), a utility function to get Bayesian models un-fitted from
    the data, representing the priors only.

Changes to functions

  - ci() supports emmeans - both Bayesian and frequentist ( #312 - cross
    fix with parameters)

Bug fixes

  - Fixed issue with default rope range for BayesFactor models.

  - Fixed issue in collinearity-check for rope() for models with less
    than two parameters.

  - Fixed issue in print-method for mediation() with stanmvreg-models,
    which displays the wrong name for the response-value.

  - Fixed issue in effective_sample() for models with only one
    parameter.

  - rope_range() for BayesFactor models returns non-NA values ( #343 )

                 Changes in version 0.7.2 (2020-07-20)                  

New functions

  - mediation(), to compute average direct and average causal mediation
    effects of multivariate response models (brmsfit, stanmvreg).

Bug fixes

  - bayesfactor_parameters() works with R<3.6.0.

                 Changes in version 0.7.0 (2020-06-19)                  

General

  - Preliminary support for stanfit objects.

  - Added support for bayesQR objects.

Changes to functions

  - weighted_posteriors() can now be used with data frames.

  - Revised print() for describe_posterior().

  - Improved value formatting for Bayesfactor functions.

Bug fixes

  - Link transformation are now taken into account for emmeans objets.
    E.g., in describe_posterior().

  - Fix diagnostic_posterior() when algorithm is not "sampling".

  - Minor revisions to some documentations.

  - Fix CRAN check issues for win-old-release.

                 Changes in version 0.6.0 (2020-04-20)                  

Changes to functions

  - describe_posterior() now also works on
    effectsize::standardize_posteriors().

  - p_significance() now also works on parameters::simulate_model().

  - rope_range() supports more (frequentis) models.

Bug fixes

  - Fixed issue with plot() data.frame-methods of p_direction() and
    equivalence_test().

  - Fix check issues for forthcoming insight-update.

                 Changes in version 0.5.3 (2020-03-26)                  

General

  - Support for bcplm objects (package cplm)

Changes to functions

  - estimate_density() now also works on grouped data frames.

Bug fixes

  - Fixed bug in weighted_posteriors() to properly weight Intercept-only
    BFBayesFactor models.

  - Fixed bug in weighted_posteriors() when models have very low
    posterior probability ( #286 ).

  - Fixed bug in describe_posterior(), rope() and equivalence_test() for
    brmsfit models with monotonic effect.

  - Fixed issues related to latest changes in as.data.frame.brmsfit()
    from the brms package.

                 Changes in version 0.5.0 (2020-01-18)                  

General

  - Added p_pointnull() as an alias to p_MAP().

  - Added si() function to compute support intervals.

  - Added weighted_posteriors() for generating posterior samples
    averaged across models.

  - Added plot()-method for p_significance().

  - p_significance() now also works for brmsfit-objects.

  - estimate_density() now also works for MCMCglmm-objects.

  - equivalence_test() gets effects and component arguments for stanreg
    and brmsfit models, to print specific model components.

  - Support for mcmc objects (package coda)

  - Provide more distributions via distribution().

  - Added distribution_tweedie().

  - Better handling of stanmvreg models for describe_posterior(),
    diagnostic_posterior() and describe_prior().

Breaking changes

  - point_estimate(): argument centrality default value changed from
    'median' to 'all'.

  - p_rope(), previously as exploratory index, was renamed as mhdior()
    (for Max HDI inside/outside ROPE), as p_rope() will refer to
    rope(..., ci = 1) ( #258 )

Bug fixes

  - Fixed mistake in description of p_significance().

  - Fixed error when computing BFs with emmGrid based on some non-linear
    models ( #260 ).

  - Fixed wrong output for percentage-values in
    print.equivalence_test().

  - Fixed issue in describe_posterior() for BFBayesFactor-objects with
    more than one model.

                 Changes in version 0.4.0 (2019-10-20)                  

New functions / features

  - convert_bayesian_to_frequentist() Convert (refit) Bayesian model as
    frequentist

  - distribution_binomial() for perfect binomial distributions

  - simulate_ttest() Simulate data with a mean difference

  - simulate_correlation() Simulate correlated datasets

  - p_significance() Compute the probability of Practical Significance
    (ps)

  - overlap() Compute overlap between two empirical distributions

  - estimate_density(): method = "mixture" argument added for mixture
    density estimation

Bug fixes

  - Fixed bug in simulate_prior() for stanreg-models when autoscale was
    set to FALSE

                 Changes in version 0.3.0 (2019-09-22)                  

General

  - revised print()-methods for functions like rope(), p_direction(),
    describe_posterior() etc., in particular for model objects with
    random effects and/or zero-inflation component

New functions / features

  - check_prior() to check if prior is informative

  - simulate_prior() to simulate model's priors as distributions

  - distribution_gamma() to generate a (near-perfect or random) Gamma
    distribution

  - contr.bayes function for orthogonal factor coding (implementation
    from Singmann & Gronau's bfrms, used for proper prior estimation
    when factor have 3 levels or more. See Bayes factor vignette ##
    Changes to functions

  - Added support for sim, sim.merMod (from arm::sim()) and
    MCMCglmm-objects to many functions (like hdi(), ci(), eti(), rope(),
    p_direction(), point_estimate(), ...)

  - describe_posterior() gets an effects and component argument, to
    include the description of posterior samples from random effects
    and/or zero-inflation component.

  - More user-friendly warning for non-supported models in
    bayesfactor()-methods

Bug fixes

  - Fixed bug in bayesfactor_inclusion() where the same interaction
    sometimes appeared more than once (#223)

  - Fixed bug in describe_posterior() for stanreg models fitted with
    fullrank-algorithm

                 Changes in version 0.2.5 (2019-08-06)                  

Breaking changes

  - rope_range() for binomial model has now a different default (-.18;
    .18 ; instead of -.055; .055)

  - rope(): returns a proportion (between 0 and 1) instead of a value
    between 0 and 100

  - p_direction(): returns a proportion (between 0.5 and 1) instead of a
    value between 50 and 100 (#168)

  - bayesfactor_savagedickey(): hypothesis argument replaced by null as
    part of the new bayesfactor_parameters() function

New functions / features

  - density_at(), p_map() and map_estimate(): method argument added

  - rope(): ci_method argument added

  - eti(): Computes equal-tailed intervals

  - reshape_ci(): Reshape CIs between wide/long

  - bayesfactor_parameters(): New function, replacing
    bayesfactor_savagedickey(), allows for computing Bayes factors
    against a point-null or an interval-null

  - bayesfactor_restricted(): Function for computing Bayes factors for
    order restricted models

Minor changes

Bug fixes

  - bayesfactor_inclusion() now works with R < 3.6.

                 Changes in version 0.2.2 (2019-06-20)                  

Breaking changes

  - equivalence_test(): returns capitalized output (e.g., Rejected
    instead of rejected)

  - describe_posterior.numeric(): dispersion defaults to FALSE for
    consistency with the other methods

New functions / features

  - pd_to_p() and p_to_pd(): Functions to convert between probability of
    direction (pd) and p-value

  - Support of emmGrid objects: ci(), rope(),
    bayesfactor_savagedickey(), describe_posterior(), ...

Minor changes

  - Improved tutorial 2

Bug fixes

  - describe_posterior(): Fixed column order restoration

  - bayesfactor_inclusion(): Inclusion BFs for matched models are more
    inline with JASP results.

                 Changes in version 0.2.0 (2019-05-29)                  

Breaking changes

  - plotting functions now require the installation of the see package

  - estimate argument name in describe_posterior() and point_estimate()
    changed to centrality

  - hdi(), ci(), rope() and equivalence_test() default ci to 0.89

  - rnorm_perfect() deprecated in favour of distribution_normal()

  - map_estimate() now returns a single value instead of a dataframe and
    the density parameter has been removed. The MAP density value is now
    accessible via attributes(map_output)$MAP_density

New functions / features

  - describe_posterior(), describe_prior(), diagnostic_posterior():
    added wrapper function

  - point_estimate() added function to compute point estimates

  - p_direction(): new argument method to compute pd based on AUC

  - area_under_curve(): compute AUC

  - distribution() functions have been added

  - bayesfactor_savagedickey(), bayesfactor_models() and
    bayesfactor_inclusion() functions has been added

  - Started adding plotting methods (currently in the see package) for
    p_direction() and hdi()

  - probability_at() as alias for density_at()

  - effective_sample() to return the effective sample size of
    Stan-models

  - mcse() to return the Monte Carlo standard error of Stan-models

Minor changes

  - Improved documentation

  - Improved testing

  - p_direction(): improved printing

  - rope() for model-objects now returns the HDI values for all
    parameters as attribute in a consistent way

  - Changes legend-labels in plot.equivalence_test() to align plots with
    the output of the print()-method (#78)

Bug fixes

  - hdi() returned multiple class attributes (#72)

  - Printing results from hdi() failed when ci-argument had fractional
    parts for percentage values (e.g. ci = 0.995).

  - plot.equivalence_test() did not work properly for brms-models (#76).

                 Changes in version 0.1.0 (2019-04-08)                  

  - CRAN initial publication and 0.1.0 release

  - Added a NEWS.md file to track changes to the package