tiedrank

Rank adjusted for ties

Syntax

[R,TIEADJ] = tiedrank(X) [R,TIEADJ] = tiedrank(X,1) [R,TIEADJ] = tiedrank(X,0,1)

Description

[R,TIEADJ] = tiedrank(X) computes the ranks of the values in the vector X. If any X values are tied, tiedrank computes their average rank. The return value TIEADJ is an adjustment for ties required by the nonparametric tests signrank and ranksum, and for the computation of Spearman's rank correlation.

[R,TIEADJ] = tiedrank(X,1) computes the ranks of the values in the vector X. TIEADJ is a vector of three adjustments for ties required in the computation of Kendall's tau. tiedrank(X,0) is the same as tiedrank(X).

[R,TIEADJ] = tiedrank(X,0,1) computes the ranks from each end, so that the smallest and largest values get rank 1, the next smallest and largest get rank 2, etc. These ranks are used in the Ansari-Bradley test.

Examples

Counting from smallest to largest, the two 20 values are 2nd and 3rd, so they both get rank 2.5 (average of 2 and 3):

tiedrank([10 20 30 40 20])
ans =
    1.0000    2.5000    4.0000    5.0000    2.5000

Algorithms

tiedrank treats NaNs in X as missing values and ignores them. The rank of NaNs in the output argument R is NaN.

Extended Capabilities

Thread-Based Environment
Run code in the background using MATLAB® `backgroundPool` or accelerate code with Parallel Computing Toolbox™ `ThreadPool`.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Version History

Introduced before R2006a