gkwreg1.0.10 package

Generalized Kumaraswamy Regression Models for Bounded Data

AIC.gkwfit

Calculate AIC or BIC for gkwfit Objects

AIC.gkwreg

Akaike's Information Criterion for GKw Regression Models

anova.gkwfit

Compare Fitted gkwfit Models using Likelihood Ratio Tests

BIC.gkwfit

Calculate Bayesian Information Criterion (BIC) for gkwfit Objects

BIC.gkwreg

Bayesian Information Criterion for GKw Regression Models

calculate_fit_metrics

Calculate additional fit metrics for all models

coef.gkwfit

Extract Model Coefficients from a gkwfit Object

coef.gkwreg

Extract Coefficients from a Fitted GKw Regression Model

confint.gkwfit

Compute Confidence Intervals for gkwfit Parameters

create_comparison_plots

Create enhanced comparison plots of all fitted distributions

create_comparison_table

Create comparison table of fit statistics with expanded metrics

dbeta_

Density of the Beta Distribution (gamma, delta+1 Parameterization)

dbkw

Density of the Beta-Kumaraswamy (BKw) Distribution

dekw

Density of the Exponentiated Kumaraswamy (EKw) Distribution

dgkw

Density of the Generalized Kumaraswamy Distribution

dkkw

Density of the Kumaraswamy-Kumaraswamy (kkw) Distribution

dkw

Density of the Kumaraswamy (Kw) Distribution

dmc

Density of the McDonald (Mc)/Beta Power Distribution Distribution

dot-calculate_diagnostic_measures

Calculate diagnostic measures for gkwreg plots

dot-calculate_distance_tests

Calculate Distance-Based Test Statistics

dot-calculate_gof

Calculate goodness-of-fit statistics

dot-calculate_half_normal_data

Calculate half-normal plot data with envelope

dot-calculate_information_criteria

Calculate Information Criteria

dot-calculate_likelihood_statistics

Calculate Likelihood Statistics

dot-calculate_model_parameters

Calculate model parameters for the specified family

dot-calculate_moment_comparisons

Calculate Moment Comparisons

dot-calculate_prediction_metrics

Calculate Prediction Accuracy Metrics

dot-calculate_probability_plot_metrics

Calculate Probability Plot Metrics

dot-calculate_profiles

Calculate profile likelihoods

dot-calculate_residuals

Calculate residuals based on the specified type

dot-calculate_sample_moments

Calculate Sample Moments

dot-calculate_sim_residuals

Calculate residuals for simulated data

dot-calculate_theoretical_cdf

Calculate Theoretical CDF Values for GKw Family Distributions

dot-calculate_theoretical_moments

Calculate Theoretical Moments for GKw Family Distributions

dot-calculate_theoretical_pdf

Calculate Theoretical PDF Values for GKw Family Distributions

dot-calculate_theoretical_quantiles

Calculate Theoretical Quantiles for GKw Family Distributions

dot-check_and_compile_TMB_code

Check and Compile TMB Model Code with Persistent Cache

dot-convert_links_to_int

Convert Link Function Names to TMB Integers

dot-create_bar_plot

Create Bar Plot for Model Comparison

dot-create_plot_titles

Create formatted plot titles

dot-create_radar_plot

Create Radar Plot for Model Comparison

dot-create_table_plot

Create Table Plot for Model Comparison

dot-determine_start_values

Determine initial parameter values

dot-extract_model_data

Extract Model Data for GKw Regression

dot-extract_model_matrices

Extract model matrices from a gkwreg object with family-specific handl...

dot-extract_model_params

Extract model parameters from a gkwreg object with family-specific han...

dot-extract_parameter_vectors

Extract parameter vectors from parameter matrix

dot-family_to_code

Convert family string to numeric code for TMB

dot-fit_submodels_tmb

Fit submodels for the GKw family for model comparison

dot-fit_submodels

Fit submodels for comparison

dot-fit_tmb

Fit GKw family distributions using TMB

dot-format_coefficient_names

Format Coefficient Names Based on Family and Model Matrices

dot-generate_additional_plots

Generate Additional Diagnostic Plots Beyond Those in gkwfit

dot-generate_plots

Generate diagnostic plots for distribution models

dot-generate_random_samples

Generate Random Samples from GKw Family Distributions

dot-get_default_fixed

Get default fixed parameters for a family

dot-get_default_start

Get default start values for a family

dot-get_family_fixed_defaults

Get default fixed parameters for each GKw family

dot-get_family_param_info

Get family parameter information

dot-map_gkwreg_to_tmb_param

Map gkwreg parameter index to TMB parameter index

dot-plot_base_r_cooks_distance

Plot Cook's distance (base R)

dot-plot_base_r_half_normal

Plot half-normal plot (base R)

dot-plot_base_r_leverage_vs_fitted

Plot leverage vs. fitted (base R)

dot-plot_base_r_predicted_vs_observed

Plot predicted vs. observed (base R)

dot-plot_base_r_residuals_vs_index

Plot residuals vs. index (base R)

dot-plot_base_r_residuals_vs_linpred

Plot residuals vs. linear predictor (base R)

dot-plot_ggplot_cooks_distance

Plot Cook's distance (ggplot2)

dot-plot_ggplot_half_normal

Plot half-normal plot (ggplot2)

dot-plot_ggplot_leverage_vs_fitted

Plot leverage vs. fitted (ggplot2)

dot-plot_ggplot_predicted_vs_observed

Plot predicted vs. observed (ggplot2)

dot-plot_ggplot_residuals_vs_index

Plot residuals vs. index (ggplot2)

dot-plot_ggplot_residuals_vs_linpred

Plot residuals vs. linear predictor (ggplot2)

dot-plot_gkwreg_base_r

Generate diagnostic plots using base R graphics

dot-plot_gkwreg_ggplot

Generate diagnostic plots using ggplot2

dot-prepare_tmb_data

Prepare TMB Data for GKw Regression

dot-prepare_tmb_params

Prepare TMB Parameters for GKw Regression

dot-print_gof_summary

Print Formatted Summary of Goodness-of-Fit Statistics

dot-process_fixed

Process Fixed Parameters for GKw Regression

dot-process_formula_parts

Process Formula Parts from a Formula Object

dot-process_link_scale

Process Link Scales for GKw Regression

dot-process_link

Process Link Functions for GKw Regression

dot-sample_model_data

Sample model data for large datasets

dot-simulate_from_distribution

Simulate observations from a specified distribution family

dot-simulate_p_values_bootstrap

Simulate P-Values Using Parametric Bootstrap

dot-validate_and_prepare_gkwreg_diagnostics

Validate inputs and prepare diagnostic data for gkwreg plots

dot-validate_data

Validate data for GKw family distributions

dot-validate_parameters

Validate parameters for GKw family distributions

extract_gof_stats

Extract Key Statistics from gkwgof Objects

fitted.gkwreg

Extract Fitted Values from a Generalized Kumaraswamy Regression Model

generate_report

Generate R Markdown report with analysis results

get_bounded_datasets

Access datasets from bounded response regression packages

get_cdf_function

Get the CDF function for a fitted GKw distribution model

get_density_function

Get the density function for a fitted GKw distribution model

get_quantile_function

Get the quantile function for a fitted GKw distribution model

gkwfit

Fit Generalized Kumaraswamy Distribution via Maximum Likelihood Estima...

gkwfitall

Fit All or Selected Generalized Kumaraswamy Family Distributions and C...

gkwgof

Comprehensive Goodness-of-Fit Analysis for GKw Family Distributions

gkwreg

Fit Generalized Kumaraswamy Regression Models

grbeta

Gradient of the Negative Log-Likelihood for the Beta Distribution (gam...

grbkw

Gradient of the Negative Log-Likelihood for the BKw Distribution

grekw

Gradient of the Negative Log-Likelihood for the EKw Distribution

grgkw

Gradient of the Negative Log-Likelihood for the GKw Distribution

grkkw

Gradient of the Negative Log-Likelihood for the kkw Distribution

grkw

Gradient of the Negative Log-Likelihood for the Kumaraswamy (Kw) Distr...

grmc

Gradient of the Negative Log-Likelihood for the McDonald (Mc)/Beta Pow...

hsbeta

Hessian Matrix of the Negative Log-Likelihood for the Beta Distributio...

hsbkw

Hessian Matrix of the Negative Log-Likelihood for the BKw Distribution

hsekw

Hessian Matrix of the Negative Log-Likelihood for the EKw Distribution

hsgkw

Hessian Matrix of the Negative Log-Likelihood for the GKw Distribution

hskkw

Hessian Matrix of the Negative Log-Likelihood for the kkw Distribution

hskw

Hessian Matrix of the Negative Log-Likelihood for the Kw Distribution

hsmc

Hessian Matrix of the Negative Log-Likelihood for the McDonald (Mc)/Be...

list_bounded_datasets

List all available datasets for bounded response regression

llbeta

Negative Log-Likelihood for the Beta Distribution (gamma, delta+1 Para...

llbkw

Negative Log-Likelihood for Beta-Kumaraswamy (BKw) Distribution

llekw

Negative Log-Likelihood for the Exponentiated Kumaraswamy (EKw) Distri...

llgkw

Negative Log-Likelihood for the Generalized Kumaraswamy Distribution

llkkw

Negative Log-Likelihood for the kkw Distribution

llkw

Negative Log-Likelihood of the Kumaraswamy (Kw) Distribution

llmc

Negative Log-Likelihood for the McDonald (Mc)/Beta Power Distribution

logLik.gkwfit

Extract Log-Likelihood from a gkwfit Object

logLik.gkwreg

Extract Log-Likelihood from a Generalized Kumaraswamy Regression Model

nrgkw

Enhanced Newton-Raphson Optimization for GKw Family Distributions

pbeta_

CDF of the Beta Distribution (gamma, delta+1 Parameterization)

pbkw

Cumulative Distribution Function (CDF) of the Beta-Kumaraswamy (BKw) D...

pekw

Cumulative Distribution Function (CDF) of the EKw Distribution

pgkw

Generalized Kumaraswamy Distribution CDF

pipe

Pipe operator

pkkw

Cumulative Distribution Function (CDF) of the kkw Distribution

pkw

Cumulative Distribution Function (CDF) of the Kumaraswamy (Kw) Distrib...

plot.gkwfit

Plot Diagnostics for a gkwfit Object

plot.gkwfitall

Plot method for gkwfitall objects

plot.gkwgof

Plot Method for gkwgof Objects

plot.gkwreg

Diagnostic Plots for Generalized Kumaraswamy Regression Models

plotcompare

Compare Goodness-of-Fit Results Across Multiple Models

pmc

CDF of the McDonald (Mc)/Beta Power Distribution

predict.gkwreg

Predictions from a Fitted Generalized Kumaraswamy Regression Model

print.anova.gkwfit

S3 method for class 'anova.gkwfit'

print.gkwfit

Print Method for gkwfit Objects

print.gkwfitall

Print method for gkwfitall objects

print.gkwgof

Print Method for gkwgof Objects

print.summary.gkwfit

Print Method for summary.gkwfit Objects

print.summary.gkwfitall

Print method for summary.gkwfitall objects

print.summary.gkwgof

Print Method for summary.gkwgof Objects

print.summary.gkwreg

Print Method for Generalized Kumaraswamy Regression Summaries

qbeta_

Quantile Function of the Beta Distribution (gamma, delta+1 Parameteriz...

qbkw

Quantile Function of the Beta-Kumaraswamy (BKw) Distribution

qekw

Quantile Function of the Exponentiated Kumaraswamy (EKw) Distribution

qgkw

Generalized Kumaraswamy Distribution Quantile Function

qkkw

Quantile Function of the Kumaraswamy-Kumaraswamy (kkw) Distribution

qkw

Quantile Function of the Kumaraswamy (Kw) Distribution

qmc

Quantile Function of the McDonald (Mc)/Beta Power Distribution

rbeta_

Random Generation for the Beta Distribution (gamma, delta+1 Parameteri...

rbkw

Random Number Generation for the Beta-Kumaraswamy (BKw) Distribution

rekw

Random Number Generation for the Exponentiated Kumaraswamy (EKw) Distr...

residuals.gkwreg

Extract Residuals from a Generalized Kumaraswamy Regression Model

rgkw

Generalized Kumaraswamy Distribution Random Generation

rkkw

Random Number Generation for the kkw Distribution

rkw

Random Number Generation for the Kumaraswamy (Kw) Distribution

rmc

Random Number Generation for the McDonald (Mc)/Beta Power Distribution

summary.gkwfit

Summary Method for gkwfit Objects

summary.gkwfitall

Summary method for gkwfitall objects

summary.gkwgof

Summary Method for gkwgof Objects

summary.gkwreg

Summary Method for Generalized Kumaraswamy Regression Models

vcov.gkwfit

Extract Variance-Covariance Matrix from a gkwfit Object

vcov.gkwreg

Extract Variance-Covariance Matrix from a Generalized Kumaraswamy Regr...

Implements regression models for bounded continuous data in the open interval (0,1) using the five-parameter Generalized Kumaraswamy distribution. Supports modeling all distribution parameters (alpha, beta, gamma, delta, lambda) as functions of predictors through various link functions. Provides efficient maximum likelihood estimation via Template Model Builder ('TMB'), offering comprehensive diagnostics, model comparison tools, and simulation methods. Particularly useful for analyzing proportions, rates, indices, and other bounded response data with complex distributional features not adequately captured by simpler models.

  • Maintainer: Lopes J. E.
  • License: MIT + file LICENSE
  • Last published: 2025-07-09