Plot Diagnostic Summaries

Creates diagnostic histograms for a fitted model.

Usage

plot_diagnostics(fit)

Arguments

fit

A fitted model object.

Value

A named list of ggplot2 objects.

Details

Diagnostic plots can be used to assess:

• Residual distributions

• Parameter estimates

• Model fit quality

• Potential outliers

These plots are useful for evaluating whether model assumptions appear reasonable and for identifying problematic fits.

See also

plot_fit, plot_residuals, flag_model, fit_groot

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_groot(
  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

plot_diagnostics(
  fit
)
#> $R2
#> Warning: Removed 1 row containing non-finite outside the scale range (`stat_bin()`).

#> 
#> $RMSE
#> Warning: Removed 1 row containing non-finite outside the scale range (`stat_bin()`).

#> 
#> $AIC
#> Warning: Removed 1 row containing non-finite outside the scale range (`stat_bin()`).

#>