Marginaleffects

* `hypotheses()`: The `FUN` argument handles `group` columns gracefully.
* Native support for `Amelia` for multiple imputation.

Documentation:

* New section on "Complex aggregations" in the Hypothesis testing vignette.

Bug fix:

* Results of the `predictions()` function could be inaccurate when (a) running version 0.15.0, (b) `type` is `NULL` or `invlink(link)`, (c) model is `glm()`, and (d) the `hypothesis` argument is non-numeric. Thanks to strengejacke for report [903](https://github.com/vincentarelbundock/marginaleffects/issues/903)

New:

* Conformal prediction via `inferences()`
* `hypothesis` argument now accepts multiple string formulas.
* The `type` argument now accepts an explicit `invlink(link)` value instead of silently back-transforming. Users are no longer pointed to `type_dictionary`. Instead, they should call their function with a bad `type` value, and they will obtain a list of valid types. The default `type` value is printed in the output. This is useful because the default `type` value is `NULL`, so the user often does not explicitly decide.
* Allow install with Rcpp 1.0.0 and greater.

Support new models:

* `survey::svyolr()`

Misc:

* `inferences(method="simulation")` uses the original point estimate rather than the mean of the simulation distribution. Issue 851.
* Better documentation and error messages for `newdata=NULL`
* Some performance improvements for `predictions()` and `marginalmeans()` (880, 882, etiennebacher).

Bug fix:

* `newdata="median"` returned mean of binary variables. Thanks to jkhanson1970 for report 896.

Breaking changes:

* Row order of the output changes for some objects. Rows are not sorted alphabetically by `term`, `by`, and variables explicitly supplied to `datagrid`. This can affect hypothesis tests computed using the b1, b2, b3, and other indices.
* New procedure `numderiv` argument use a different procedure to select the step size used in the finite difference numeric derivative used to compute standard errors: abs(x) * sqrt(.Machine$double.eps). The numerical results may not be exactly identical to previous versions of `marginaleffects`, but the step size should be adequate in a broader variety of cases. Note that users can use the `numderiv` argument for more control on numeric differentiation, as documented.
* `bife` models are no longer supported pending investigation in weird results in the tests. Looking for volunteers write more thorough tests.

New:

* Support: `logistf` package.
* Support: `DCchoice` package.
* Support: `stats::nls`
* `hypotheses()` can now accept raw data frame, which gives a lot of flexibility for custom contrasts and functions. See the Hypothesis vignette for an example.
* `numderiv` argument allows users to use finite difference (center or forward) or Richardson's method to compute the numerical derivatives used in the calculation of standard errors.

Bug fixes:

* `inferences()` supports the `cross` argument for `comparisons()` objects. Thanks to Kirill Solovev for report 856.
* `splines::bs()` in formulas could produce incorrect results due to weirdness in `stats::model.matrix()`. Thanks to chiungming for report 831.
* `mgcv` with `ocat` are now supported. Thanks to Lorenzo Fabbri for Issue 844.
* `quantreg` problem with `rowid` merge did not affect estimates but did not return the full original data. Issue 829.
* `get_modeldata()` extracts weights variable when available.
* `predictions()` is no longer broken in some `inferences()` calls. Issue 853
* Inaccurate averaging with `comparison=differenceavg` some models where all predictors are categorical. Thanks to Karl Ove Hufthammer for report 865.

Misc:

* Major refactor to simplify the code base and make maintenance easier.

Breaking change:

* `glmmTMB`: Standard errors are no longer supported because they may have been erroneous. Follow Issue 810 on Github for developments: https://github.com/vincentarelbundock/marginaleffects/issues/810

New:

* `hypothesis` argument accepts wildcards: `hypothesis = "b*=b1"`
* `s.value` column in all output: Shannon transforms for p values. See Greenland (2019).
* `marginal_means` supports `mira` (`mice` objects).
* `comparisons()`: The `variables` arguments now accepts arbitrary numeric vectors of length equal to the number of rows in `newdata`. This allows users to specify fully custom treatment sizes. In the documentation examples, we show how to estimate the difference for a 1 standard deviation shift in a regressor, where the standard deviation is calculated on a group-wise basis.
* `comparisons()`: the `variables` argument now accepts "revpairwise", "revsequential", "revreference" for factor and character variables.
* `comparisons()`: the `comparison` argument now accept "lift" and "liftavg".

Performance:

* Computing elasticities for linear models is now up to 30% faster (787, etiennebacher).

Bug fixes:

* Better handling of environments when `newdata` is a function call. Thanks to jcccf for report 814 and to capnrefsmmat for the proposed fix using the `rlang` package.
* Degrees of freedom mismatch for joint hypothesis tests. Thanks to snhansen for report 789.

Breaking change:

* Row order of output has changed for many calls, especially those using the `by` argument. This may break hypothesis tests conducted by indexing `b1`, `b2`, etc. This was necessary to fix Issue 776. Thanks to marcora for the report.

New:

* `hypotheses()`: Joint hypothesis tests (F and Chi-square) with the `joint` and `joint_test` arguments.
* `vcov.hypotheses` method.
* `wts` is now available in `plot_predictions()`, `plot_comparisons()`, and `plot_slopes()`.

Bug:

* Wrong order of rows in bayesian models with `by` argument. Thanks to shirdekel for report 782.

* `vcov()` and `coef()` methods for `marginaleffects` objects.
* Strings in `wts` are accepted with the `by` argument.
* `predictions()` and `avg_predictions()` no longer use an automatic backtransformation for GLM models unless `hypothesis` is `NULL`.
* `vcov()` can be used to retrieve a full variance-covariance matrix from objects produced by `comparisons()`, `slopes()`, `predictions()`, or `marginal_means()` objects.
* When processing objects obtained using `mice` multiple imputation, the pooled model using `mice::pool` is attached to the `model` attribute of the output. This means that functions like `modelsummary::modelsummary()` will not erroneously report goodness-of-fit statistics from just a single model and will instead appropriately report the statistics for the pooled model. Thanks to Tristan-Siegfried for PR 740.
* More informative error messages on some prediction problems. Thanks to andymilne for Report 751.

Performance:

* `inferences()` is now up to 17x faster and much more memory-efficient when `method` is `"boot"` or `"rsample"` (770, 771, etiennebacher).

Bugs:

* `brms` models with `nl=TRUE` and a single predictor generated an error. Thanks to Tristan-Siegried for Report 759.
* `avg_predictions()`: Incorrect group-wise averaging when all predictors are categorical, the `variables` variable is used, and we are averaging with `avg_` or the `by` argument. Thanks to BorgeJorge for report 766.
* Bug when `datagrid()` when called inside a user-written function. Thanks to NickCH-K for report 769 and to capnrefsmmat for the diagnostics.