The case study dataset is about growth performance and abattoir findings in pigs commercial production in a selected set of 15 Canadian farms collected in March 1987.
An adapted data frame of the original dataset which consists of 341 observations of 8 variables and a grouping variable (farm).
presence of atrophic rhinitis.
presence of moderate to severe pneumonia.
sex of the pig (1=female, 0=castrated).
presence of liver damage (parasite-induced white spots).
presence of fecal/gastrointestinal nematode eggs at time of slaughter.
count of nematodes in small intestine at time of slaughter.
days elapsed from birth to slaughter (days).
average daily weight gain (grams).
When using the data to fit an additive Bayesian network, the variables
eggs are considered binomial,
adg Gaussian. The variable
farm can be used
to adjust for grouping.
Kratzer, G., Lewis, F.I., Comin, A., Pittavino, M. and Furrer, R. (2019). "Additive Bayesian Network Modelling with the R Package abn". arXiv preprint arXiv:1911.09006.
Dohoo, Ian Robert, Wayne Martin, and Henrik Stryhn. Veterinary epidemiologic research. No. V413 DOHv. Charlottetown, Canada: AVC Incorporated, 2003.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.