models_EMOTIONS

A data frame containing the daily milk yield for 100 individuals up to 210 days in milk

datasets

internal

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'

models_EMOTIONS function

A data frame with 47 rows and 5 variables:<ul>
<li>Model: Model description</li>
<li>Model_acronym: Model acronym used in the EMOTIONS functions</li>
<li>Authors: List of authors of each model available in EMOTIONS</li>
<li>Year: Year of publication of each model available in EMOTIONS</li>
<li>Reference: Link to the original publication of each model available in EMOTIONS</li>
</ul>

models_EMOTIONS: A data frame containing the daily milk yield for 100 individuals up to 210 days in milk

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Examples