Keyword : Rank

F01BLF	Pseudo-inverse and rank of real $m$ by $n$ matrix $(m \geq n)$
F04JGF	Least squares (if rank $= n$ ) or minimal least squares (if rank $< n$ ) solution of $m$ real equations in $n$ unknowns, $m \geq n$
G01DHF	Ranks, Normal scores, approximate Normal scores or exponential (Savage) scores
G02BNF	Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data
G02BPF	Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data
G02BQF	Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data
G02BRF	Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data
G02BSF	Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values
G08AGF	Performs the Wilcoxon one-sample (matched pairs) signed rank test
G08RAF	Regression using ranks, uncensored data
G08RBF	Regression using ranks, right-censored data
M01DAF	Rank a vector, real numbers
M01DBF	Rank a vector, integer numbers
M01DCF	Rank a vector, character data
M01DEF	Rank rows of a matrix, real numbers
M01DFF	Rank rows of a matrix, integer numbers
M01DJF	Rank columns of a matrix, real numbers
M01DKF	Rank columns of a matrix, integer numbers
M01DZF	Rank arbitrary data
M01EAF	Rearrange a vector according to given ranks, real numbers
M01EBF	Rearrange a vector according to given ranks, integer numbers
M01ECF	Rearrange a vector according to given ranks, character data
M01EDF	Rearrange a vector according to given ranks, complex numbers

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Keyword Index for the NAG Library Manual

NAG Library Manual