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Summary of Logistic Fits

Source: R/summary.logistic_fit.R
summary.logistic_fit.Rd

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.

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)

  • 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.

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
)
#> 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 model summary
#> ----------------------
#> Total bottles: 24
#> Successful fits: 24
#> Failed fits: 0
#> Low R-squared (< 0.90): 7
#> Lambda at boundary: 9
#>