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Download a pdf copy of this help file here |
See also: Correlation in ModelRisk, VoseSpearman,Rank order correlation, The non-parametric Bootstrap
VoseSpearmanU({known_ys},{known_xs})
This function simulates the uncertainty about the Spearman rank correlation coefficient between two variables using non-parametric Bootstrap.
{known_ys} - a list of observations for the first variable
{known_xs} - a list of observations for the second variable
Spearman's rank correlation coefficient (a.k.a. Spearman's rho) is a non-parametric measure of the degree of correspondence between two variables. Like Kendall's tau, Spearman's rank correlation is carried out on the ranks of the data, i.e. what position (rank) the data point takes in an ordered list from the minimum to maximum values, rather than the actual data values themselves.
The sample estimator of Spearman's rho is defined by:
Example model