.fit_submodels

internal

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.

Lopes J. E.

gkwreg

Generalized Kumaraswamy Regression Models for Bounded Data

.fit_submodels function

<dl><dt>data</dt>
<dd>Numeric vector with values in the (0, 1) interval.</dd>
<dt>result</dt>
<dd>Main fit result.</dd>
<dt>fit</dt>
<dd>Estimation method: "tmb" or "nr".</dd>
<dt>method</dt>
<dd>Optimization method (for TMB): "nlminb" or "optim".</dd>
<dt>hessian</dt>
<dd>Logical; if TRUE, computes standard errors and covariance matrix.</dd>
<dt>optimizer.control</dt>
<dd>List of control parameters for the optimizer.</dd>
<dt>silent</dt>
<dd>Logical; if TRUE, suppresses messages.</dd></dl>

Arguments

Fit submodels for comparison — .fit_submodels

<dl>

<dt>data</dt>
<dd>Numeric vector with values in the (0, 1) interval.</dd>


<dt>result</dt>
<dd>Main fit result.</dd>


<dt>fit</dt>
<dd>Estimation method: "tmb" or "nr".</dd>


<dt>method</dt>
<dd>Optimization method (for TMB): "nlminb" or "optim".</dd>


<dt>hessian</dt>
<dd>Logical; if TRUE, computes standard errors and covariance matrix.</dd>


<dt>optimizer.control</dt>
<dd>List of control parameters for the optimizer.</dd>


<dt>silent</dt>
<dd>Logical; if TRUE, suppresses messages.</dd>

</dl>

.fit_submodels: Fit submodels for comparison

Description

Usage

Value

Arguments