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strengejacke committed Jul 13, 2024
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the null model fails, or when you already have fit the null model and want
to save time.

* `icc()` and `r2_nakagawa()` get a `approximation` argument indicating the
* `icc()` and `r2_nakagawa()` get a `approximation` argument indicating the
approximation method for the distribution-specific (residual) variance. See
Nakagawa et al. 2017 for details.

* `icc()` and `r2_nakagawa()` get a `model_component` argument indicating the
* `icc()` and `r2_nakagawa()` get a `model_component` argument indicating the
component for zero-inflation or hurdle models.

* `performance_rmse()` (resp. `rmse()`) can now compute analytical and
* `performance_rmse()` (resp. `rmse()`) can now compute analytical and
bootstrapped confidence intervals. The function gains following new arguments:
`ci`, `ci_method` and `iterations`.

* New function `r2_ferrari()` to compute Ferrari & Cribari-Neto's R2 for
* New function `r2_ferrari()` to compute Ferrari & Cribari-Neto's R2 for
generalized linear models, in particular beta-regression.

## Bug fixes

* Fixed issue in `check_model()` when model contained a transformed response
variable that was named like a valid R function name (e.g., `lm(log(lapply) ~ x)`,
when data contained a variable named `lapply`).

# performance 0.12.0

## Breaking
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* Improved documentation and new vignettes added.

* `check_model()` gets a `base_size` argument, to set the base font size for plots.
* `check_model()` gets a `base_size` argument, to set the base font size for plots.

* `check_predictions()` for `stanreg` and `brmsfit` models now returns plots in
the usual style as for other models and no longer returns plots from
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# performance 0.10.6

## General
## General

* Support for `nestedLogit` models.

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* `model_performance()`, `check_overdispersion()`, `check_outliers()` and `r2()`
now work with objects of class `fixest_multi` (@etiennebacher, #554).

* `model_performance()` can now return the "Weak instruments" statistic and
p-value for models of class `ivreg` with `metrics = "weak_instruments"`
(@etiennebacher, #560).
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* Fixed issues in `check_model()` for models with convergence issues that lead
to `NA` values in residuals.
* Fixed bug in `check_outliers` whereby passing multiple elements to the

* Fixed bug in `check_outliers` whereby passing multiple elements to the
threshold list generated an error (#496).

* `test_wald()` now warns the user about inappropriate F test and calls
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* `check_normality()`, `check_homogeneity()` and `check_symmetry()` now works
for `htest` objects.

* Print method for `check_outliers()` changed significantly: now states the
methods, thresholds, and variables used, reports outliers per variable (for
univariate methods) as well as any observation flagged for several
variables/methods. Includes a new optional ID argument to add along the
* Print method for `check_outliers()` changed significantly: now states the
methods, thresholds, and variables used, reports outliers per variable (for
univariate methods) as well as any observation flagged for several
variables/methods. Includes a new optional ID argument to add along the
row number in the output (@rempsyc #443).

* `check_outliers()` now uses more conventional outlier thresholds. The `IQR`
* `check_outliers()` now uses more conventional outlier thresholds. The `IQR`
and confidence interval methods now gain improved distance scores that
are continuous instead of discrete.

## Bug Fixes

* Fixed wrong *z*-score values when using a vector instead of a data frame in
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## Changes to functions

* `check_model()` gains a `show_dots` argument, to show or hide data points.
* `check_model()` gains a `show_dots` argument, to show or hide data points.
This is particular useful for models with many observations, where generating
the plot would be very slow.

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* Fixed issue in `check_heteroscedasticity()` for *aov* objects.

* Fixed issues for *lmrob* and *glmrob* objects.

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