plotcompare: Compare Goodness-of-Fit Results Across Multiple Models

In gkwreg: Generalized Kumaraswamy Regression Models for Bounded Data

Compare Goodness-of-Fit Results Across Multiple Models

Description

Creates a comparison of goodness-of-fit statistics and plots across multiple models from the GKw family of distributions.

Usage

plotcompare(gof_list, criteria = "all", plot = TRUE, plot_type = "all", ...)

Arguments

gof_list	A named list of gkwgof objects, where names are used as model identifiers.
criteria	Character vector specifying which criteria to compare. Available options are: "information" (for AIC, BIC, etc.), "distance" (for KS, CvM, AD, etc.), "prediction" (for MAE, RMSE, etc.), "probability" (for P-P, Q-Q correlations), or "all" for all criteria. Default is "all".
plot	Logical; if TRUE, creates comparison plots. Default is TRUE.
plot_type	Character string specifying the type of plot to create. Available options are: "radar" for a radar chart (requires the fmsb package), "bar" for bar charts, "table" for a formatted table, or "all" for all plot types. Default is "all".
...	Additional arguments to be passed to plotting functions.

Value

A list containing the comparison results and plots.

Examples

# Generate sample data
set.seed(123)
data <- rkw(n = 200, alpha = 2.5, beta = 1.8)

# Fit multiple models
fit_kw <- gkwfit(data, family = "kw")
fit_beta <- gkwfit(data, family = "beta")
fit_gkw <- gkwfit(data, family = "gkw")

# Calculate goodness-of-fit statistics for each model
gof_kw <- gkwgof(fit_kw, print_summary = FALSE)
gof_beta <- gkwgof(fit_beta, print_summary = FALSE)
gof_gkw <- gkwgof(fit_gkw, print_summary = FALSE)

# Compare the models
comparison <- plotcompare(
  list(KW = gof_kw, Beta = gof_beta, GKW = gof_gkw),
  plot_type = "all"
)

gkwreg documentation built on April 16, 2025, 1:10 a.m.