##### swh:1:snp:2c68a6c5a8af2f06ac2c0225927f25b54fd1f9d0

Tip revision:

**ebb4d406af6a7168582caf0094830bc559b472a7**authored by**Dominique Makowski**on**02 May 2022, 06:40:03 UTC****version 0.12.1** Tip revision:

**ebb4d40**NEWS.md

```
# 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 = .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
```