Create reports for model comparison as obtained by the
performance::compare_performance()
function in the performance package.
Usage
# S3 method for class 'compare_performance'
report(x, ...)
# S3 method for class 'compare_performance'
report_table(x, ...)
# S3 method for class 'compare_performance'
report_statistics(x, table = NULL, ...)
# S3 method for class 'compare_performance'
report_parameters(x, table = NULL, ...)
# S3 method for class 'compare_performance'
report_text(x, table = NULL, ...)Arguments
- x
Object of class
NEW OBJECT.- ...
Arguments passed to or from other methods.
- table
Provide the output of
report_table()to avoid its re-computation.
Value
An object of class report().
See also
Specific components of reports (especially for stats models):
Other types of reports:
Methods:
Template file for supporting new models:
Examples
# \donttest{
library(report)
library(performance)
m1 <- lm(Sepal.Length ~ Petal.Length * Species, data = iris)
m2 <- lm(Sepal.Length ~ Petal.Length + Species, data = iris)
m3 <- lm(Sepal.Length ~ Petal.Length, data = iris)
x <- performance::compare_performance(m1, m2, m3)
r <- report(x)
r
#> We compared three models; lm (R2 = 0.84, adj. R2 = 0.83, AIC = 106.77, BIC =
#> 127.84, RMSE = 0.33, Sigma = 0.34), lm (R2 = 0.84, adj. R2 = 0.83, AIC =
#> 106.23, BIC = 121.29, RMSE = 0.33, Sigma = 0.34) and lm (R2 = 0.76, adj. R2 =
#> 0.76, AIC = 160.04, BIC = 169.07, RMSE = 0.40, Sigma = 0.41).
summary(r)
#> We compared three models; lm (adj. R2 = 0.83, BIC = 127.84), lm (adj. R2 =
#> 0.83, BIC = 121.29) and lm (adj. R2 = 0.76, BIC = 169.07).
as.data.frame(r)
#> Name | Model | AIC (weights) | AICc (weights) | BIC (weights) | R2
#> --------------------------------------------------------------------
#> m1 | lm | 106.8 (0.43) | 107.6 (0.39) | 127.8 (0.04) | 0.84
#> m2 | lm | 106.2 (0.57) | 106.6 (0.61) | 121.3 (0.96) | 0.84
#> m3 | lm | 160.0 (<.001) | 160.2 (<.001) | 169.1 (<.001) | 0.76
#>
#> Name | R2 (adj.) | RMSE | Sigma
#> -------------------------------
#> m1 | 0.83 | 0.33 | 0.34
#> m2 | 0.83 | 0.33 | 0.34
#> m3 | 0.76 | 0.40 | 0.41
summary(as.data.frame(r))
#> Name | Model | AIC (weights) | AICc (weights) | BIC (weights) | R2
#> --------------------------------------------------------------------
#> m1 | lm | 106.8 (0.43) | 107.6 (0.39) | 127.8 (0.04) | 0.84
#> m2 | lm | 106.2 (0.57) | 106.6 (0.61) | 121.3 (0.96) | 0.84
#> m3 | lm | 160.0 (<.001) | 160.2 (<.001) | 169.1 (<.001) | 0.76
#>
#> Name | R2 (adj.) | RMSE
#> -----------------------
#> m1 | 0.83 | 0.33
#> m2 | 0.83 | 0.33
#> m3 | 0.76 | 0.40
# Specific reports
report_table(x)
#> Name | Model | AIC (weights) | AICc (weights) | BIC (weights) | R2
#> --------------------------------------------------------------------
#> m1 | lm | 106.8 (0.43) | 107.6 (0.39) | 127.8 (0.04) | 0.84
#> m2 | lm | 106.2 (0.57) | 106.6 (0.61) | 121.3 (0.96) | 0.84
#> m3 | lm | 160.0 (<.001) | 160.2 (<.001) | 169.1 (<.001) | 0.76
#>
#> Name | R2 (adj.) | RMSE | Sigma
#> -------------------------------
#> m1 | 0.83 | 0.33 | 0.34
#> m2 | 0.83 | 0.33 | 0.34
#> m3 | 0.76 | 0.40 | 0.41
report_statistics(x)
#> R2 = 0.84, adj. R2 = 0.83, AIC = 106.77, BIC = 127.84, RMSE = 0.33, Sigma = 0.34
#> R2 = 0.84, adj. R2 = 0.83, AIC = 106.23, BIC = 121.29, RMSE = 0.33, Sigma = 0.34
#> R2 = 0.76, adj. R2 = 0.76, AIC = 160.04, BIC = 169.07, RMSE = 0.40, Sigma = 0.41
report_parameters(x)
#> - lm (R2 = 0.84, adj. R2 = 0.83, AIC = 106.77, BIC = 127.84, RMSE = 0.33, Sigma = 0.34)
#> - lm (R2 = 0.84, adj. R2 = 0.83, AIC = 106.23, BIC = 121.29, RMSE = 0.33, Sigma = 0.34)
#> - lm (R2 = 0.76, adj. R2 = 0.76, AIC = 160.04, BIC = 169.07, RMSE = 0.40, Sigma = 0.41)
# }