# scaled PCA of Anderson iris measurements
iris[, -5] %>%
princomp(cor = TRUE) %>%
as_tbl_ord() %>%
mutate_rows(species = iris$Species) %>%
print() -> iris_pca
# row-principal biplot with centroid-based stars
iris_pca %>%
ggbiplot(aes(color = species)) +
theme_bw() +
scale_color_brewer(type = "qual", palette = 2) +
stat_rows_star(alpha = .5, fun = "mean") +
geom_rows_point(alpha = .5) +
stat_rows_center(fun = "mean", size = 4, shape = 1L) +
ggtitle(
"Row-principal PCA biplot of Anderson iris measurements",
"Segments connect each observation to its within-species centroid"
)
# row-principal biplot with depth median-based stars
iris_pca %>%
ggbiplot(aes(color = species)) +
theme_bw() +
scale_color_brewer(type = "qual", palette = 2) +
stat_rows_star(alpha = .5, fun.ord = "depth_median") +
geom_rows_point(alpha = .5) +
stat_rows_center(fun.ord = "depth_median", size = 4, shape = 1L) +
ggtitle(
"Row-principal PCA biplot of Anderson iris measurements",
"Segments connect each observation to its within-species depth median"
)
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