Performance metrics

Source: R/cv-model-fit.R

Returns named vector of the most common performance metrics

performance_metrics(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  na.rm = FALSE
)

Arguments

observed

Numeric vector
predicted

Numeric vector
SESOI_lower

Lower smallest effect size of interest threshold
SESOI_upper

Upper smallest effect size of interest threshold
na.rm

Should NAs be removed? Default is FALSE

Examples

m1 <- lm_model(
  predictors = iris[2:3],
  outcome = iris[[1]]
)

predicted <- generic_predict(m1)

performance_metrics(
  observed = iris[[1]],
  predicted = predicted
)
#>           MBE           MAE          RMSE          PPER SESOI to RMSE 
#>   -0.02708721    0.33614908    0.41204534    0.00000000    0.00000000 
#>     R-squared        MinErr        MaxErr     MaxAbsErr 
#>    0.75181012   -1.07734504    1.08398244    1.08398244