qad (version 0.1.2)

heatmap.qad: Heatmap of dependence measures

Description

The pairwise computed dependence measures (output of the function pairwise.qad()) are illustrated by a heatmap.

Usage

heatmap.qad(
  pw_qad,
  select = c("dependence", "mean.dependence", "asymmetry"),
  fontsize = 4,
  significance = FALSE,
  sign.level = 0.05,
  scale = "abs",
  color = "plasma",
  rb_values = c(10, 0.315, 0.15)
)

Arguments

pw_qad

output of the function pairwise.qad().

select

a character indicating which dependence value is plotted. Options are c("dependence", "mean.dependence", "asymmetry").

fontsize

a numeric specifying the font size of the values.

significance

a logical indicating whether significant values - with respect to the permutated p.values - are marked with a star.

sign.level

numeric value indicating the significance level.

scale

character indicating whether the heatmap uses a relative or absolute scale. Options are "rel" or "abs" (default).

color

Select the color palette. Options are c("plasma" (default), "viridis", "inferno", "magma", "cividis").

rb_values

a vector of size 3 with number of values, start value and end value in the rainbow colors space.

Value

a heatmap

Details

If the output of pairwise.qad() contains p-values, significant values can be highlighted by stars by setting significance=TRUE.

Examples

# NOT RUN {
n <- 1000
x <- runif(n, 0, 1)
y <- x^2 + rnorm(n, 0, 1)
z <- runif(n, 0, 1)
sample_df <- data.frame(x, y, z)

#qad (Not Run)
model <- pairwise.qad(sample_df, permutation = FALSE)
heatmap.qad(model, select = "dependence", fontsize = 6)
# }