easystats/performance: performance 0.10.9

Published February 17, 2024 | Version v0.10.9

Software Open

Changes

r2() for models of class glmmTMB without random effects now returns the correct r-squared value for non-mixed models.
check_itemscale() now also accepts data frames as input. In this case, factor_index must be specified, which must be a numeric vector of same length as number of columns in x, where each element is the index of the factor to which the respective column in x.
check_itemscale() gets a print_html() method.
Clarification in the documentation of the estimator argument for performance_aic().
Improved plots for overdispersion-checks for negative-binomial models from package glmmTMB (affects check_overdispersion() and check_mnodel()).
Improved detection rates for singularity in check_singularity() for models from package glmmTMB.
For model of class glmmTMB, deviance residuals are now used in the check_model() plot.
Improved (better to understand) error messages for check_model(), check_collinearity() and check_outliers() for models with non-numeric response variables.
r2_kullback() now gives an informative error for non-supported models.

Fixed issue in binned_residuals() for models with binary outcome, where in rare occasions empty bins could occur.
performance_score() should no longer fail for models where scoring rules can't be calculated. Instead, an informative message is returned.
check_outliers() now properly accept the percentage_central argument when using the "mcd" method.
Fixed edge cases in check_collinearity() and check_outliers() for models with response variables of classes Date, POSIXct, POSIXlt or difftime.
Fixed issue with check_model() for models of package quantreg.

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easystats/performance-v0.10.9.zip md5:db7508c70319445a747c50acce367655	4.6 MB	Preview Download

Is supplement to: Software: https://github.com/easystats/performance/tree/v0.10.9 (URL)