performance: Compare performance of different models

In flexFitR: Flexible Non-Linear Least Square Model Fitting

Compare performance of different models

Description

Computes indices of model performance for different models at once and hence allows comparison of indices across models.

Usage

performance(..., metrics = "all", metadata = FALSE, digits = 2)

Arguments

...	Multiple model objects (only of class 'modeler').
metrics	Can be "all" or a character vector of metrics to be computed (one or more of "logLik", "AIC", "AICc", "BIC", "Sigma", "SSE", "MAE", "MSE", "RMSE", "R2"). "all" by default.
metadata	Logical. If TRUE, metadata is included with the performance metrics. Default is FALSE.
digits	An integer. The number of decimal places to round the output. Default is 2.

Value

A data.frame with performance metrics for models in (...).

Examples

library(flexFitR)
data(dt_potato)
# Model 1
mod_1 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_lin_plat",
    parameters = c(t1 = 45, t2 = 80, k = 90),
    subset = 40
  )
print(mod_1)
# Model 2
mod_2 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_logistic",
    parameters = c(a = 0.199, t0 = 47.7, k = 100),
    subset = 40
  )
print(mod_2)
# Model 3
mod_3 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_lin",
    parameters = c(m = 20, b = 2),
    subset = 40
  )
print(mod_3)
performance(mod_1, mod_2, mod_3, metrics = c("AIC", "AICc", "BIC", "Sigma"))

flexFitR documentation built on April 16, 2025, 5:09 p.m.