# 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.

# bayestestR 0.13.2

## 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.

# bayestestR 0.13.1

## 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.

# bayestestR 0.13.0

## 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.


# bayestestR 0.12.1

## 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 `n`s.

* 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.

# bayestestR 0.11.5

* Fixes failing tests in CRAN checks.

# bayestestR 0.11.1

## New functions

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

# bayestestR 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 ).

# bayestestR 0.10.0

## 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.

# bayestestR 0.9.0

## Breaking

* The default `ci` width has been changed to 0.95 instead of 0.89 (see
  [here](https://github.com/easystats/bayestestR/discussions/250)). 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()`.

# bayestestR 0.8.2

## 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 ).

# bayestestR 0.8.0

## 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).

# bayestestR 0.7.5

## 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 )

# bayestestR 0.7.2

## 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`.

# bayestestR 0.7.0

## 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.

# bayestestR 0.6.0

## 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.

# bayestestR 0.5.3

## 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.

# bayestestR 0.5.0

## 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.

# bayestestR 0.4.0

## 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`

# bayestestR 0.3.0

## 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`](https://github.com/bayesstuff/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

# bayestestR 0.2.5

## 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](https://github.com/easystats/bayestestR/issues/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`.

# bayestestR 0.2.2

## 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.

# bayestestR 0.2.0

## 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`](https://github.com/easystats/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).

# bayestestR 0.1.0

- CRAN initial publication and [0.1.0
  release](https://github.com/easystats/bayestestR/releases/tag/v0.1.0)

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