fit_logistic: Fit Logistic model

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

Fit Logistic model

Description

Fits a Logistic gas-production model to each bottle in a rumen_gp dataset.

Usage

fit_logistic(data, start = NULL)

Arguments

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

Details

Equation

V(t) = \frac{A} { 1+\exp \left[ 2+ 4k(\lambda-t) \right] }

where:

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

• A is asymptotic gas production

• k is the fractional rate constant

• \lambda is lag time

Interpretation

The Logistic model describes gas production using a sigmoidal curve with an initial lag phase, a period of rapid fermentation, and a plateau approaching the asymptotic gas production.

The parameter k controls the steepness of the curve, while \lambda determines the position of the sigmoid along the time axis.

Advantages

• Explicit lag parameter

• Smooth sigmoidal behavior

• Stable convergence

• Widely used in biological growth and fermentation studies

Limitations

• Assumes a symmetric sigmoidal curve

• May not adequately fit highly asymmetric fermentation profiles

• Less flexible than Gompertz or Dual Logistic models

Value

A logistic_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_logistic(
  gp
)

summary(fit_default)

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

summary(fit_custom_start)

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