calculatePearsonResiduals

Computes the Pearson residuals based on the observed values, fitted means, and the approximate variance of the distribution.

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

calculatePearsonResiduals function

<dl><dt>y</dt>
<dd>NumericVector of observations.</dd>
<dt>fitted</dt>
<dd>NumericVector of fitted values (means).</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 Pearson Residuals — calculatePearsonResiduals

<dl>

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


<dt>fitted</dt>
<dd>NumericVector of fitted values (means).</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>

calculatePearsonResiduals: Calculate Pearson Residuals

Description

Usage

Value

Arguments