calculateQuantileResiduals

Computes quantile residuals by transforming the cumulative distribution function (CDF) values to the standard normal quantiles.

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

calculateQuantileResiduals function

<dl><dt>y</dt>
<dd>NumericVector of observations.</dd>
<dt>params</dt>
<dd>NumericMatrix with parameters (columns: alpha, beta, gamma, delta, lambda).</dd>
<dt>family</dt>
<dd>String specifying the distribution family (default: "gkw").</dd></dl>

Arguments

Calculate Quantile Residuals — calculateQuantileResiduals

<dl>

<dt>y</dt>
<dd>NumericVector of observations.</dd>


<dt>params</dt>
<dd>NumericMatrix with parameters (columns: alpha, beta, gamma, delta, lambda).</dd>


<dt>family</dt>
<dd>String specifying the distribution family (default: "gkw").</dd>

</dl>

calculateQuantileResiduals: Calculate Quantile Residuals

Description

Usage

Value

Arguments