Statistics Toolbox

Functions for Data with Missing Values (NaNs)

Most real-world data sets have one or more missing elements. It is convenient to code missing entries in a matrix as NaN (Not a Number).

Here is a simple example.

m = magic(3);
m([1 5]) = [NaN NaN]
m =
    NaN      1      6
      3    NaN      7
      4      9      2

Any arithmetic operation that involves the missing values in this matrix yields NaN, as below.

sum(m)
ans =
    NaN   NaN     15

Removing cells with NaN would destroy the matrix structure. Removing whole rows that contain NaN would discard real data. Instead, the Statistics Toolbox has a variety of functions that are similar to other MATLAB functions, but that treat NaN values as missing and therefore ignore them in the calculations.

nansum(m)
ans =
     7    10    13

NaN Functions
nanmax	Maximum ignoring NaNs
nanmean	Mean ignoring NaNs
nanmedian	Median ignoring NaNs
nanmin	Minimum ignoring NaNs
nanstd	Standard deviation ignoring NaNs
nansum	Sum ignoring NaNs

In addition, other Statistics Toolbox functions operate only on the numeric values, ignoring NaNs. These include iqr, kurtosis, mad, prctile, range, skewness, and trimmean.

Measures of Dispersion

Function for Grouped Data