.simulate_from_distribution

Simulate observations from a specified distribution family

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

.simulate_from_distribution function

<dl><dt>n</dt>
<dd>Number of observations to simulate</dd>
<dt>alphaVec</dt>
<dd>Vector of alpha parameters</dd>
<dt>betaVec</dt>
<dd>Vector of beta parameters</dd>
<dt>gammaVec</dt>
<dd>Vector of gamma parameters</dd>
<dt>deltaVec</dt>
<dd>Vector of delta parameters</dd>
<dt>lambdaVec</dt>
<dd>Vector of lambda parameters</dd>
<dt>family</dt>
<dd>Character string specifying distribution family</dd></dl>

Arguments

Simulate observations from a specified distribution family — .simulate_from_distribution

<dl>

<dt>n</dt>
<dd>Number of observations to simulate</dd>


<dt>alphaVec</dt>
<dd>Vector of alpha parameters</dd>


<dt>betaVec</dt>
<dd>Vector of beta parameters</dd>


<dt>gammaVec</dt>
<dd>Vector of gamma parameters</dd>


<dt>deltaVec</dt>
<dd>Vector of delta parameters</dd>


<dt>lambdaVec</dt>
<dd>Vector of lambda parameters</dd>


<dt>family</dt>
<dd>Character string specifying distribution family</dd>

</dl>

.simulate_from_distribution: Simulate observations from a specified distribution family

Description

Usage

Value

Arguments