## Simulated data examples:
dummy <- rnbinom(1000, size = 1.5, prob = 0.8)
Ord_plot(dummy)
## Real data examples:
data("HorseKicks")
data("Federalist")
data("Butterfly")
data("WomenQueue")
if (FALSE) {
grid.newpage()
pushViewport(viewport(layout = grid.layout(2, 2)))
pushViewport(viewport(layout.pos.col=1, layout.pos.row=1))
Ord_plot(HorseKicks, main = "Death by horse kicks", newpage = FALSE)
popViewport()
pushViewport(viewport(layout.pos.col=1, layout.pos.row=2))
Ord_plot(Federalist, main = "Instances of 'may' in Federalist papers", newpage = FALSE)
popViewport()
pushViewport(viewport(layout.pos.col=2, layout.pos.row=1))
Ord_plot(Butterfly, main = "Butterfly species collected in Malaya", newpage = FALSE)
popViewport()
pushViewport(viewport(layout.pos.col=2, layout.pos.row=2))
Ord_plot(WomenQueue, main = "Women in queues of length 10", newpage = FALSE)
popViewport(2)
}
## same
mplot(
Ord_plot(HorseKicks, return_grob = TRUE, main = "Death by horse kicks"),
Ord_plot(Federalist, return_grob = TRUE, main = "Instances of 'may' in Federalist papers"),
Ord_plot(Butterfly, return_grob = TRUE, main = "Butterfly species collected in Malaya"),
Ord_plot(WomenQueue, return_grob = TRUE, main = "Women in queues of length 10")
)
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