Rankings and Rank Correlations
This package implements various strategies for computing ranks and rank correlations.
StatsBase.ordinalrank
— Function.ordinalrank(x; lt = isless, rev::Bool = false)
Return the ordinal ranking ("1234" ranking) of an array. The lt
keyword allows providing a custom "less than" function; use rev=true
to reverse the sorting order. All items in x
are given distinct, successive ranks based on their position in sort(x; lt = lt, rev = rev)
. Missing values are assigned rank missing
.
StatsBase.competerank
— Function.competerank(x; lt = isless, rev::Bool = false)
Return the standard competition ranking ("1224" ranking) of an array. The lt
keyword allows providing a custom "less than" function; use rev=true
to reverse the sorting order. Items that compare equal are given the same rank, then a gap is left in the rankings the size of the number of tied items - 1. Missing values are assigned rank missing
.
StatsBase.denserank
— Function.denserank(x)
Return the dense ranking ("1223" ranking) of an array. The lt
keyword allows providing a custom "less than" function; use rev=true
to reverse the sorting order. Items that compare equal receive the same ranking, and the next subsequent rank is assigned with no gap. Missing values are assigned rank missing
.
StatsBase.tiedrank
— Function.tiedrank(x)
Return the tied ranking, also called fractional or "1 2.5 2.5 4" ranking, of an array. The lt
keyword allows providing a custom "less than" function; use rev=true
to reverse the sorting order. Items that compare equal receive the mean of the rankings they would have been assigned under ordinal ranking. Missing values are assigned rank missing
.
StatsBase.corspearman
— Function.corspearman(x, y=x)
Compute Spearman's rank correlation coefficient. If x
and y
are vectors, the output is a float, otherwise it's a matrix corresponding to the pairwise correlations of the columns of x
and y
.
StatsBase.corkendall
— Function.corkendall(x, y=x)
Compute Kendall's rank correlation coefficient, τ. x
and y
must both be either matrices or vectors.