Apply a function on each pair of features
Value
a list containing the output of applying the function to each feature pair.
See ?base::mapply()
Examples
web <- randomWeb(10)
# For each feature pair, was the value for x higher than the value for y?
pairwise_gt <- pairwiseApply(
X = web,
FUN = function(x, y) x > y,
MoreArgs = NULL, SIMPLIFY = FALSE, USE.NAMES = TRUE
)
head(pairwise_gt)
#> $x_1y_1
#> [1] TRUE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE FALSE
#>
#> $x_1y_2
#> [1] TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
#>
#> $x_1y_4
#> [1] TRUE TRUE FALSE FALSE TRUE TRUE TRUE FALSE TRUE TRUE
#>
#> $x_1y_5
#> [1] TRUE TRUE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE
#>
#> $x_1y_9
#> [1] TRUE TRUE TRUE TRUE TRUE FALSE FALSE FALSE FALSE TRUE
#>
#> $x_1y_10
#> [1] TRUE TRUE TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE
#>
# Run cor.test() on each pair of features
pairwise_cor <- pairwiseApply(
X = web,
FUN = function(x, y) cor.test(x, y),
MoreArgs = NULL, SIMPLIFY = FALSE, USE.NAMES = TRUE
)
pairwise_cor[1]
#> $x_1y_1
#>
#> Pearson's product-moment correlation
#>
#> data: x and y
#> t = 0.39731, df = 8, p-value = 0.7015
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#> -0.5376084 0.7068238
#> sample estimates:
#> cor
#> 0.1391034
#>
#>