## General

`r2()`

now works for more regression models.
`r2_bayes()`

now works for multivariate response models.
`model_performance()`

now works for more regression models, and also includes the log-loss, proper scoring rules and percentage of correct predictions as new metric for models with binary outcome.

`performance_accuracy()`

, which calculates the predictive accuracy of linear or logistic regression models.
`performance_logloss()`

to compute the log-loss of models with binary outcome. The log-loss is a proper scoring function comparable to the `rmse()`

.
`performance_score()`

to compute the logarithmic, quadratic and spherical proper scoring rules.
`performance_pcp()`

to calculate the percentage of correct predictions for models with binary outcome.
`performance_roc()`

, to calculate ROC-curves.
`performance_aicc()`

, to calculate the second-order AIC (AICc).

## New check-functions

`check_collinearity()`

to calculate the variance inflation factor and check model predictors for multicollinearity.
`check_outliers()`

to check models for influential observations.
`check_heteroscedasticity()`

to check models for (non-)constant error variance.
`check_normality()`

to check models for (non-)normality of residuals.
`check_autocorrelation()`

to check models for auto-correlated residuals.
`check_distribution()`

to classify the distribution of a model-family using machine learning.

## New indices-functions

`r2_mckelvey()`

to compute McKelvey and Zavoinas R2 value.
`r2_zeroinflated()`

to compute R2 for zero-inflated (non-mixed) models.
`r2_xu()`

as a crude R2 measure for linear (mixed) models.

## Breaking changes

`model_performance.stanreg()`

and `model_performance.brmsfit()`

now only return one R2-value and its standard error, instead of different (robust) R2 measures and credible intervals.
`error_rate()`

is now integrated in the `performance_pcp()`

-function.

## Changes to functions

`model_performance.stanreg()`

and `model_performance.brmsfit()`

now also return the *WAIC* (widely applicable information criterion).
`r2_nakagawa()`

now calculates the full R2 for mixed models with zero-inflation.
`icc()`

now returns `NULL`

and no longer stops when no mixed model is provided.
`compare_performance()`

now shows the Bayes factor when all compared models are of same class.
- Some functions get a
`verbose`

-argument to sow or suppress warnings.

## Bug fixes

- Renamed
`r2_coxnell()`

to `r2_coxsnell()`

.
- Fix issues in
`r2_bayes()`

and `model_performance()`

for ordinal models resp. models with cumulative link (#48).
`compare_performance()`

did not sort the `name`

-column properly, if the columns `class`

and `name`

were not in the same alphabetical order (#51).