plot_steepness_regression {EloSteepness}

plot steepness regression

Description

visually combine individual scores with group-level steepness

Usage

plot_steepness_regression(
  x,
  adjust = 3,
  color = TRUE,
  width_fac = 0.1,
  axis_extend = 0.1
)

Arguments

x

result from elo_steepness_from_matrix, elo_steepness_from_sequence or davids_steepness

adjust

numeric, parameter for smoothing posterior of individual scores

color

logical, default is TRUE where individuals get color- coded. If FALSE: a gray scale is used. It is also possible to hand over a vector with colors, which then must be correspond in length to the number of individuals.

width_fac

numeric, relative width of posterior distributions. This is actually affects the 'height' but since the posteriors are rotated it visually represents width.

axis_extend

numeric, an extension factor to extend the horizontal axis to leave space for the posteriors. When set to 0 the axis stops at n (the number of individuals, which represents the lowest rank).

Value

a plot

Examples

data("bonobos", package = "EloRating")
res <- davids_steepness(bonobos, refresh = 0, iter = 1000)
plot_steepness_regression(res, width_fac = 0.5)