Skip to contents

Summary of LEL Fits

Source: R/summary.lel_fit.R
summary.lel_fit.Rd

Summarizes parameter estimates and goodness-of-fit statistics for a fitted LEL model.

Usage

# S3 method for class 'lel_fit'
summary(object, ...)

Arguments

object

A lel_fit object.

...

Additional arguments passed to methods.

Value

A data frame containing parameter estimates and model diagnostics for each fitted bottle.

Details

The summary typically includes:

  • Asymptotic gas production (A)

  • Fractional rate constant (k)

  • Shape parameter (d)

  • Lag time (lambda)

  • Residual Sum of Squares (RSS)

  • Root Mean Squared Error (RMSE)

  • R-squared (R²)

  • Akaike Information Criterion (AIC)

  • Bayesian Information Criterion (BIC)

The LEL (Logistic-Exponential with Lag) model combines exponential fermentation kinetics with a logistic component and an explicit lag phase.

The lag parameter (lambda) represents the delay before substantial fermentation begins, while the shape parameter (d) controls curve flexibility.

This combination makes the LEL model suitable for describing complex sigmoidal fermentation profiles with delayed onset.

See also

fit_lel, fit_le0, plot_fit, plot_residuals, compare_models

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
)

fit <- fit_lel(
  gp
)
#> Warning: Large negative pressure values detected. Minimum PSI = -1.274 . Please inspect the affected bottles.
#> rumenGP data validation passed.
#> Observations: 1752
#> Heads: 24
#> Treatments: 5

summary(
  fit
)
#> 
#> Logistic-Exponential (LEL) model summary
#> ----------------------------------------
#> Total bottles: 24
#> Successful fits: 23
#> Failed fits: 1
#> Low R-squared (< 0.90): 11
#> Lambda at boundary: 11
#>