# Poisson regression of yarn weaving data
warpbreaks %>%
glm(formula = breaks ~ wool + tension, family = "poisson") %>%
as_tbl_ord() %>%
augment_ord() %>%
print() -> warpbreaks_pois
# summarize ordination
glance(warpbreaks_pois)
# regression biplot with nonlinear isolines
warpbreaks_pois %>%
ggbiplot(aes(
x = tensionM, y = tensionH, intercept = `(Intercept)`, label = .name
)) +
theme_bw() + theme_biplot() +
geom_jitter(stat = "rows", width = .1, height = .1) +
geom_cols_vector() +
geom_cols_text_radiate() +
geom_cols_isolines(family = poisson(), by = 5)
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