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Summary of Dual Logistic Fits

Source: R/summary.dual_logistic_fit.R
summary.dual_logistic_fit.Rd

Summarizes parameter estimates and goodness-of-fit statistics for a fitted dual-pool logistic model.

Usage

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

Arguments

object

A dual_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:

  • Rapid pool gas volume (V1F)

  • Slow pool gas volume (V2F)

  • Rapid pool rate constant (k1)

  • Slow pool rate constant (k2)

  • 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 Dual Logistic model partitions fermentation into rapidly and slowly degradable fractions, providing a biologically informative description of fermentation dynamics.

See also

fit_dual_logistic, plot_dual_pools, plot_fit, 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_dual_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
)
#> 
#> Dual-pool Logistic model summary
#> --------------------------------
#> Total bottles: 24
#> Successful fits: 20
#> Failed fits: 4
#> Low R-squared (< 0.90): 0
#> Lambda at boundary: 1
#>