.calculate_prediction_metrics

Calculate Prediction Accuracy Metrics

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

.calculate_prediction_metrics function

<dl><dt>p_empirical</dt>
<dd>Numeric vector of empirical CDF values</dd>
<dt>p_theoretical</dt>
<dd>Numeric vector of theoretical CDF values</dd></dl>

Arguments

Calculate Prediction Accuracy Metrics — .calculate_prediction_metrics

<dl>

<dt>p_empirical</dt>
<dd>Numeric vector of empirical CDF values</dd>


<dt>p_theoretical</dt>
<dd>Numeric vector of theoretical CDF values</dd>

</dl>

.calculate_prediction_metrics: Calculate Prediction Accuracy Metrics

Description

Usage

Value

Arguments