mean_removing_outli​ers_Tukey(X, RMZEROVALS)

Compute Mean and St.Dev. after outliers' removal (Tukey's criterion)


Updated 15 May 2017

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[M,SD,Cx] = mean_removing_outliers_Tukey(X,RMZEROVALS)

Compute the robust mean (M) and the standard deviation (SD)
of a given vector or matrix (X). The resulting values are considered robust as they are
computed ITERATIVELY removing those observations that are classified as outliers.
Outliers are identified using "Tukey's Boxplot" method, where observation Xi
is considered outlier if Xi < Q1 - 1.5·IQR or Xi > Q3 + 1.5·IQR.
NOTE: NaN values are excluded from the computation.


X : vector
RMZEROVALS : if '1', zero values are removed from the
computation. default RMZEROVALS is 0, meaning that
zero values are used in the computation.


M : Robust mean (i.e. computed after outliers removal)
SD : Robust Standard Deviation (i.e. computed after outliers removal)
Cx : vector of the conserved (i.e. non-outliers) observations

Cite As

Ruggero G. Bettinardi (2023). mean_removing_outliers_Tukey(X, RMZEROVALS) (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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