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@gsimpson.bsky.social Oct 6, 2026, 9:01 AM

📝 My paper on generalized additive models (GAMs) in animal science is out! Learn nonlinear relationships from data, estimate growth rates and compare treatments, with cows, pigs and quail + reproducible #RStats code.

Open access: doi.org/10.1016/j.an...

#mgcv #AnimalScience #Statistics 🧪

Eight panels show body mass over 78 days for 57 Japanese quail. Columns represent control, T4, T3 and combined T3–T4 hormone treatments; rows separate females and males. Coloured points are measurements, lines are individual growth curves fitted by a hierarchical generalized additive model, and shading shows 95% credible intervals. Growth slows towards a plateau, with females generally reaching higher body masses than males.

Eighteen panels show individual pig growth curves. Black points mark daily average weight estimates from a depth camera; blue lines show curves fitted by a hierarchical generalized additive model, with shaded 95% credible intervals. Weights generally increase over time, with differences in growth and measurement variability among pigs. Uncertainty widens where measurements are sparse or absent.

Four-panel comparison of models fitted to a cow’s average daily milk fat production. Observations rise to a peak around weeks 8–10, then decline. The first panel shows fitted curves and uncertainty bands for Wood’s model, a Tweedie GLM and a Tweedie GAM. Residual plots show curved patterns for Wood’s model and the GLM, but little remaining pattern for the GAM.

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