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model_performance.lm

Performance of Regression Models


Description

Compute indices of model performance for regression models.

Usage

## S3 method for class 'lm'
model_performance(model, metrics = "all", verbose = TRUE, ...)

Arguments

model

A model.

metrics

Can be "all", "common" or a character vector of metrics to be computed (some of c("AIC", "AICc", "BIC", "R2", "R2_adj", "RMSE", "SIGMA", "LOGLOSS", "PCP", "SCORE")). "common" will compute AIC, BIC, R2 and RMSE.

verbose

Toggle off warnings.

...

Arguments passed to or from other methods.

Details

Depending on model, following indices are computed:

  • AIC Akaike's Information Criterion, see ?stats::AIC

  • AICc Second-order (or small sample) AIC with a correction for small sample sizes

  • BIC Bayesian Information Criterion, see ?stats::BIC

  • R2 r-squared value, see r2

  • R2_adj adjusted r-squared, see r2

  • RMSE root mean squared error, see performance_rmse

  • SIGMA residual standard deviation, see get_sigma()

  • LOGLOSS Log-loss, see performance_logloss

  • SCORE_LOG score of logarithmic proper scoring rule, see performance_score

  • SCORE_SPHERICAL score of spherical proper scoring rule, see performance_score

  • PCP percentage of correct predictions, see performance_pcp

Value

A data frame (with one row) and one column per "index" (see metrics).

Examples

model <- lm(mpg ~ wt + cyl, data = mtcars)
model_performance(model)

model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
model_performance(model)

performance

Assessment of Regression Models Performance

v0.7.1
GPL-3
Authors
Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>)
Initial release

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