Le Monde rank test (cont’d)

April 5, 2010
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(This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers)

Following a comment from efrique pointing out that this statistic is called Spearman footrule, I want to clarify the notation in

mathfrak{M}_n = sum_{i=1}^n |r^x_i-r^y_i|,,

namely (a) that the ranks of x_i and y_i are considered for the whole sample, i.e.

{r^x_1,ldots,r^x_n,r^y_1,ldots,r^y_n} = {1,ldots,2n}

instead of being computed separately for the x‘s and the y‘s, and then (b) that the ranks are reordered for each group (meaning that the groups could be of different sizes). This statistics is therefore different from the Spearman footrule studied by Persi Diaconis and R. Graham in a 1977 JRSS paper,

mathfrak{D}_ n = sum_{i=1}^n |pi(i)-sigma(i)|,,

where pi and sigma are permutations from mathfrak{S}_n. The mean of mathfrak{D}_ n is approximately n^2/3. I mistakenly referred to Spearman’s rho rank correlation test in the previous post. It is actually much more related to the Siegel-Tukey test, even though I think there exists a non-parametric test of iid-ness for paired observations… The x‘s and the y‘s are thus not paired, despite what I wrote previously. This distance must be related to some non-parametric test for checking the equality of location parameters.


Filed under: R, Statistics Tagged: non-parametrics, Persi Diaconis, Spearman footrule, Spearman rank test

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