{ "_id": "6a1bde4a1d7bb097a0a17a5e", "Package": "EMOTIONS", "Type": "Package", "Title": "Ensemble Models for Lactation Curves", "Version": "1.3", "Authors@R": "c(person(given = \"Pablo\",\nfamily = \"Fonseca\",\nrole = c(\"aut\", \"cre\"),\nemail = \"p.fonseca@csic.es\"),person(\"Marcos\", \"Prates\", email = \"marcosop@gmail.com\", role = \"aut\"),\nperson(\"Aroa\", \"Suarez-Vega\", email = \"asuav@unileon.es\", role = \"aut\"),\nperson(\"Ruth Arribas\", \"Gonzalo\", email = \"rarrg@unileon.es\", role = \"aut\"),\nperson(\"Beatriz\", \"Gutierrez-Gil\", email = \"beatriz.gutierrez@unileon.es\", role = \"aut\"),\nperson(\"Juan José\", \"Arranz\", email = \"jjarrs@unileon.es\", role = \"aut\"))", "Description": "Lactation curves describe temporal changes in milk yield\nand are key to breeding and managing dairy animals more\nefficiently. The use of ensemble modeling, which consists of\ncombining predictions from multiple models, has the potential\nto yields more accurate and robust estimates of lactation\npatterns than relying solely on single model estimates. The\npackage EMOTIONS fits 47 models for lactation curves and\ncreates ensemble models using model averaging based on Akaike\ninformation criterion (AIC), Bayesian information criterion\n(BIC), root mean square percentage error (RMSPE) and mean\nsquared error (MAE), variance of the predictions, cosine\nsimilarity for each model's predictions, and Bayesian Model\nAverage (BMA). The daily production values predicted through\nthe ensemble models can be used to estimate resilience\nindicators in the package. The package allows the graphical\nvisualization of the model ranks and the predicted lactation\ncurves. Additionally, the packages allows the user to detect\nmilk loss events and estimate residual-based resilience\nindicators.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-31 07:04:29 UTC", "User": "root" }, "Author": "Pablo Fonseca [aut, cre], Marcos Prates [aut], Aroa Suarez-Vega\n[aut], Ruth Arribas Gonzalo [aut], Beatriz Gutierrez-Gil [aut],\nJuan José Arranz [aut]", "Maintainer": "Pablo Fonseca ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-04-01 21:04:06 UTC", "RemoteUrl": "https://github.com/cran/EMOTIONS", "RemoteRef": "HEAD", "RemoteSha": "9b5b5dd3456f1f00dc7fd61893969e26e2972f71", "MD5sum": "f581b5c84492bcb8409da740728941c4", "_user": "cran", "_type": "src", "_file": "EMOTIONS_1.3.tar.gz", "_fileid": "ed67b820ec938da3e8fe6796fac66b95c84ed9d24318765d05a9174667fb788f", "_filesize": 1422622, "_sha256": 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"imp_my", "LacCurveFit", "milkloss_detect", "ModelRankRange", "PlotMilkLoss", "PlotWeightLac", "ResInd", "RidgeModels" ], "_datasets": [ { "name": "LacData", "title": "A data frame containing the daily milk yield for 100 individuals up to 210 days in milk", "object": "LacData", "class": [ "data.frame" ], "fields": [ "ID", "DIM", "DMY" ], "rows": 21550, "table": true, "tojson": true }, { "name": "model_pars", "title": "A data frame containing the models included in the EMOTIONS package that can have the parameters edited", "object": "model_pars", "class": [ "data.frame" ], "fields": [ "Model_acronym", "Parameters" ], "rows": 42, "table": true, "tojson": true }, { "name": "models_EMOTIONS", "title": "A data frame containing the daily milk yield for 100 individuals up to 210 days in milk", "object": "models_EMOTIONS", "class": [ "data.frame" ], "fields": [ "Model", "Model_acronym", "Authors", "Year", "Reference" ], "rows": 47, "table": true, "tojson": true } ], "_help": [ { "page": "imp_my", "title": "Impute missing daily milk yields using the ensemble created", "topics": [ "imp_my" ] }, { "page": "LacCurveFit", "title": "A wrap function to the ModelsLac function that allows the fit of lactation curve models based on daily production and days in milk records simultaneously for a list of animals", "topics": [ "LacCurveFit" ] }, { "page": "milkloss_detect", "title": "Identify milk loss events and resilience indicators from daily milk yields", "topics": [ "milkloss_detect" ] }, { "page": "ModelRankRange", "title": "Create a line plot that shows the range of the ranks obtained for each model across the individuals", "topics": [ "ModelRankRange" ] }, { "page": "ModelsLac", "title": "Performs the model fitting and the weight assignment based on different strategies for each individual ID", "topics": [ "ModelsLac" ] }, { "page": "PlotMilkLoss", "title": "Plot the actual daily milk daily production and the predicted values highlighting the detected milk loss events", "topics": [ "PlotMilkLoss" ] }, { "page": "PlotWeightLac", "title": "Plot the actual daily milk daily production and the predicted values obtained by the ensemble model", "topics": [ "PlotWeightLac" ] }, { "page": "ResInd", "title": "A function to estimate resilience estimators (logarithm of variance, lag1 autocorrelation and skewness) based on daily milk production records", "topics": [ "ResInd" ] }, { "page": "RidgeModels", "title": "The function RidgeModels allows the visualization of the distribution of model's ranks across individuals using ridge density plots", "topics": [ "RidgeModels" ] } ], "_readme": "https://github.com/cran/EMOTIONS/raw/HEAD/README.md", "_rundeps": [ "bayestestR", "cli", "cpp11", "datawizard", "dplyr", "farver", "generics", "ggplot2", "ggridges", "glue", "gtable", "insight", "isoband", "labeling", "lattice", "lifecycle", "magrittr", "MASS", "Matrix", "MatrixModels", "minpack.lm", "orthopolynom", "parameters", "pillar", "pkgconfig", "polynom", "purrr", 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S. 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