Generalized Kumaraswamy Regression Models for Bounded Data
Extract Formula from GKw Regression Model
Get Call from GKw Regression Model
Control Parameters for Generalized Kumaraswamy Regression
Fit Generalized Kumaraswamy Regression Models
Extract Log-Likelihood from Generalized Kumaraswamy Regression Models
Likelihood Ratio Test for Nested GKw Models
Extract Model Frame from GKw Regression Model
Extract Model Matrix from GKw Regression Model
Number of Observations for GKw Regression Models
Pipe operator
Diagnostic Plots for Generalized Kumaraswamy Regression Models
Predictions from a Fitted Generalized Kumaraswamy Regression Model
Print Method for ANOVA of GKw Models
Print Method for Generalized Kumaraswamy Regression Models
Print Method for Generalized Kumaraswamy Regression Summaries
Extract Residuals from a Generalized Kumaraswamy Regression Model
Extract Response Variable from GKw Regression Model
Summary Method for Generalized Kumaraswamy Regression Models
Extract Terms from GKw Regression Model
Update and Re-fit a GKw Regression Model
Extract Variance-Covariance Matrix from a Generalized Kumaraswamy Regr...
Process Link Scales for GKw Regression
Process Link Functions for GKw Regression
Validate Data for GKw Regression
Extract Family from GKw Regression Model
Extract Fitted Values from a Generalized Kumaraswamy Regression Model
Akaike Information Criterion for GKw Regression Models
Analysis of Deviance for GKw Regression Models
Bayesian Information Criterion for GKw Regression Models
Extract Coefficients from a Fitted GKw Regression Model
Confidence Intervals for Generalized Kumaraswamy Regression Parameters
Check and Compile TMB Model Code with Persistent Cache
Convert Link Function Names to TMB Integers
Extract Model Data for GKw Regression
Format Coefficient Names Based on Family and Model Matrices
Get Parameter Information for a GKw Family Distribution
Prepare TMB Data for GKw Regression
Prepare TMB Parameters for GKw Regression
Process Fixed Parameters for GKw Regression
Process Formula Parts from a Formula Object
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.
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