RANKS gives the rank of each element in a vector. This program uses an advanced algorithm with averge effort O(m.n.log(n)) NaN in the input yields NaN in the output. r = ranks(X[,DIM]) if X is a vector, return the vector of ranks of X adjusted for ties. if X is matrix, the rank is calculated along dimension DIM. if DIM is zero or empty, the lowest dimension with more then 1 element is used. r = ranks(X,DIM,'traditional') implements the traditional algorithm with O(n^2) computational and O(n^2) memory effort r = ranks(X,DIM,'mtraditional') implements the traditional algorithm with O(n^2) computational and O(n) memory effort r = ranks(X,DIM,'advanced ') implements an advanced algorithm with O(n*log(n)) computational and O(n.log(n)) memory effort see also: CORRCOEF, SPEARMAN, RANKCORR REFERENCES: --

- mean MEAN calculates the mean of data elements.
- ranks RANKS gives the rank of each element in a vector.

- corrcoef CORRCOEF calculates the correlation matrix from pairwise correlations.
- naninsttest NANINSTTEST checks whether the functions from NaN-toolbox have been
- rankcorr RANKCORR calculated the rank correlation coefficient.
- ranks RANKS gives the rank of each element in a vector.
- tiedrank TIEDRANK compute rank of samples, the mean value is used in case of ties

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