calculatePartialResiduals

Computes partial residuals for a selected covariate by adding the product of the regression coefficient and
the corresponding design matrix value to the raw residual.

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

calculatePartialResiduals function

<dl><dt>y</dt>
<dd>NumericVector of observations.</dd>
<dt>fitted</dt>
<dd>NumericVector of fitted values.</dd>
<dt>X</dt>
<dd>NumericMatrix of design matrix values.</dd>
<dt>beta</dt>
<dd>NumericVector of regression coefficients.</dd>
<dt>covariate_idx</dt>
<dd>Integer index for the selected covariate (0-indexed).</dd></dl>

Arguments

Calculate Partial Residuals — calculatePartialResiduals

<dl>

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


<dt>fitted</dt>
<dd>NumericVector of fitted values.</dd>


<dt>X</dt>
<dd>NumericMatrix of design matrix values.</dd>


<dt>beta</dt>
<dd>NumericVector of regression coefficients.</dd>


<dt>covariate_idx</dt>
<dd>Integer index for the selected covariate (0-indexed).</dd>

</dl>

calculatePartialResiduals: Calculate Partial Residuals

Description

Usage

Value

Arguments