Learn R Programming

EMOTIONS: Ensemble Models fOr lacTatION curveS

INDEX

Copy Link

Version

Install

install.packages('EMOTIONS')

Version

1.0

License

GPL-3

Maintainer

Pablo Fonseca

Last Published

June 18th, 2025

Functions in EMOTIONS (1.0)

GetLacModelsMetrics

Estimate the Akaike information criterion (AIC), Bayeasian information criterion (BIC), root mean square percentage error (RMSPE) and mean squared error (MAE) for the fitted models

Create a line plot that shows the range of the ranks obtained for each model across the individuals

Plot the actual and predicted daily milk production obtained by the ensemble model

Estimate resilience indicators (log-variance, lag-1 autocorrelation, and skewness) from daily milk production records

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

A wrapper function for the ModelsLac function that fits lactation curve models based on daily production and days in milk records simultaneously for a list of animals

Perform model fitting and weight assignment based on different strategies for each individual ID

CosSquaredWeight

Estimate normalized model weights based on the cosine similarity of each model's predictions

BMAweight_gamma

Estimate normalized model weights using an Expectation–Maximization (EM) algorithm with a gamma distribution

Estimate normalized model weights based on the variance of the predictions

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

models_EMOTIONS

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

A data frame containing the models included in the EMOTIONS package that can have the parameters edited

Define the parameters for the lactation curve models to be fitted