RidgeModels

The `RidgeModels` function creates ridge density plots to visualize the distribution of model ranks across individuals.

Lactation curve modeling plays a central role in dairy production, supporting management decisions and the selection of animals with superior productivity and resilience. The package 'EMOTIONS' fits 47 models for lactation curves and creates ensemble models using model averaging based on Akaike information criterion, Bayesian information criterion, root mean square percentage error, and mean squared error, variance of the predictions, cosine similarity for each model's predictions, and Bayesian Model Average. The daily production values predicted through the ensemble models can be used to estimate resilience indicators in the package. Additionally, the package allows the graphical visualization of the model ranks and the predicted lactation curves.

Pablo Fonseca

EMOTIONS

'EMOTIONS: Ensemble Models for Lactation Curves'

RidgeModels function

<dl><dt>LacCurveFit</dt>
<dd>The object returned by the `LacCurveFit` function</dd>
<dt>metric</dt>
<dd>The name of the metric used to plot the model ranks</dd></dl>

Arguments

Visualize the distribution of model ranks across individuals using ridge density plots — RidgeModels

<dl>

<dt>LacCurveFit</dt>
<dd>The object returned by the `LacCurveFit` function</dd>


<dt>metric</dt>
<dd>The name of the metric used to plot the model ranks</dd>

</dl>

RidgeModels: Visualize the distribution of model ranks across individuals using ridge density plots

Description

Usage

Value

Arguments