compare_models_by_treatment: Compare Models by Treatment

In rumenGP: Rumen Gas Production Modeling, Comparison, and Visualization

Compare Models by Treatment

Description

Calculates model performance separately for each treatment.

Usage

compare_models_by_treatment(...)

Arguments

...	Fitted model objects.

Details

Performance metrics are computed using treatment-level predictions and observations, allowing direct comparison of competing models within each treatment.

Typical metrics include:

• R-squared (R²)

• Root Mean Squared Error (RMSE)

• Residual Sum of Squares (RSS)

• Akaike Information Criterion (AIC)

• Bayesian Information Criterion (BIC)

This function is useful for determining whether different treatments are best described by different kinetic models.

Value

A data frame containing treatment-level performance metrics for each fitted model.

See Also

compare_models, rank_models_by_treatment, best_model_by_treatment, model_win_frequency

Examples

files <- example_data()

raw_data <- read_ankom(
  files$ankom
)

metadata <- read_metadata(
  files$metadata
)

gp <- process_ankom(
  raw_data,
  metadata,
  headspace_ml = 210,
  temperature_c = 39
)

groot_fit <- fit_groot(
  gp
)

gompertz_fit <- fit_gompertz(
  gp
)

compare_models_by_treatment(
  Groot = groot_fit,
  Gompertz = gompertz_fit
)

rumenGP documentation built on Oct. 2, 2026, 5:09 p.m.