fit_lel: Fit Logistic-Exponential model (LEL)

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

Fit Logistic-Exponential model (LEL)

Description

Fits the Logistic-Exponential model with an explicit lag phase.

Usage

fit_lel(data, start = NULL)

Arguments

data	A rumen_gp object.
start	Optional list of starting values. May contain any of: A k d lambda

Details

Equation

V(t) = \frac{ A \left( 1-e^{-k(t-\lambda)} \right) } { 1+\exp \left[ \ln\left(\frac{1}{d}\right) - k(t-\lambda) \right] }

where:

• V(t) is cumulative gas production at time t

• A is asymptotic gas production

• k is the fractional rate constant

• d is a shape parameter

• \lambda is lag time

Interpretation

The LEL model combines an exponential fermentation component, a logistic component, and an explicit lag phase.

This model is more flexible than traditional exponential models and can describe complex fermentation dynamics with delayed onset of gas production.

Advantages

• Explicit lag parameter

• Flexible sigmoidal behavior

• Can represent delayed fermentation

• Often fits complex gas production profiles well

Limitations

• More parameters than EXP0 or EXPL

• Greater risk of parameter correlation

• May require careful starting values

• Increased computational complexity

Value

A lel_fit object containing:

• Parameter estimates

• Model diagnostics

• Predicted values

• Residuals

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 using package default starting values
fit_default <- fit_lel(
  gp
)

summary(fit_default)

# Fit using custom starting values
fit_custom_start <- fit_lel(
  gp,
  start = list(
    A = 120,
    k = 0.05,
    d = 0.50,
    lambda = 1
  )
)

summary(fit_custom_start)

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