How is the “std” function used in Matlab?

In MATLAB, the std function is used to calculate the standard deviation of a given set of data. Standard deviation is a method of measuring the spread of data and indicates the level of dispersion within a dataset.

The syntax of the std function is as follows:

s = std(A)
s = std(A, 'all')
s = std(A, dim)
s = std(___, nanflag)

Explanation of parameters:

1. A matrix or vector representing input data.
2. ‘All’: specifies treating the entire input data matrix as a single vector for computation.
3. dim: specifies the dimension for calculating the standard deviation. If dim is set to 1, it calculates the standard deviation for each column; if dim is set to 2, it calculates the standard deviation for each row.
4. nanflag: Specify how to handle data containing NaN values. The options are:

   – ‘omitnan’: Ignore NaN values.
   – ‘includenan’: Treat data containing NaN values as part of the standard deviation.

The output of the std function is the value of the standard deviation. If the dim parameter is used, the output will be a vector where each element represents the standard deviation on the specified dimension. If the ‘all’ parameter is used, the output will be a scalar.

Here are some examples:

A = [1 2 3 4 5];
s = std(A)    % 输出：1.5811

B = [1 2 3; 4 5 6; 7 8 9];
s = std(B)    % 输出：2.5810    2.5810    2.5810

s = std(B, 'all')    % 输出：2.7386

s = std(B, 1)    % 输出：3.2659    3.2659    3.2659

s = std(B, 2)    % 输出：0.8165    0.8165    0.8165

C = [1 NaN 3 4];
s = std(C)    % 输出：NaN

s = std(C, 'omitnan')    % 输出：1.5275

Please note that the std function in MATLAB by default uses the formula that divides by N-1 for sample standard deviation, where N is the size of the sample. If you need to use the formula that divides by N, please use std(A, ‘all’, 0) or std(A, 0).