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Kendall's tau-b rank correlation

Source: R/ops-timefreq.R
kendallTau.Rd

Kendall's tau-b, the concordance-based rank correlation: the normalised difference between concordant and discordant pairs, tie-corrected. It is the third rank-correlation method alongside Pearson's r (correlationTest, method "pearson") and Spearman's rho (method "spearman"), and is the robust choice for ordinal or heavily-tied data and small samples. The tau-b statistic and the normal-approximation p-value reproduce base R stats::cor.test(method = "kendall") and scipy.stats.kendalltau bit-for-bit.

Usage

kendallTau(x, y = NULL)

Arguments

x

Either the numeric predictor vector (with y the response), or a two-column matrix/data frame (column 1 = x, column 2 = y), or a list of two numeric vectors. Incomplete (x, y) pairs are dropped.

y

The second numeric vector when x is a single vector.

Value

A list with statistic (tau-b), p_value (two-sided, normal-approximation), z (the approximation's z-statistic) and n.

See also

correlationTest

Examples

kendallTau(c(1, 2, 3, 4, 5), c(2, 1, 4, 3, 5))
#> $statistic
#> [1] 0.6
#> 
#> $p_value
#> [1] 0.1416447
#> 
#> $z
#> [1] 1.469694
#> 
#> $n
#> [1] 5
#>