heatmap.qad {qad} | R Documentation |
The pairwise computed dependence measures (output of the function pairwise.qad()
) are illustrated by a heatmap.
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) )
pw_qad |
output of the function |
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 qad p.values - are denoted by 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. |
If the output of pairwise.qad
() contains p-values, significant values can be highlighted by stars by setting significance=TRUE.
a heatmap
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)