summary.logistic_fit: Summary of Logistic Fits

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

Summary of Logistic Fits

Description

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

Usage

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

Arguments

object	A logistic_fit object.
...	Additional arguments passed to methods.

Details

The summary typically includes:

• Asymptotic gas production (A)

• Fractional rate constant (k)

• 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 Logistic model describes gas production using a sigmoidal curve characterized by:

• An initial lag phase

• A rapid fermentation phase

• A plateau approaching asymptotic gas production

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

Value

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

See Also

fit_logistic, fit_gompertz, 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_logistic(
  gp
)

summary(
  fit
)

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