Documentation

mean

Average or mean value of array

Syntax

Description

example

M = mean(A) returns the mean of the elements of A along the first array dimension whose size does not equal 1.

  • If A is a vector, then mean(A) returns the mean of the elements.

  • If A is a matrix, then mean(A) returns a row vector containing the mean of each column.

  • If A is a multidimensional array, then mean(A) operates along the first array dimension whose size does not equal 1, treating the elements as vectors. This dimension becomes 1 while the sizes of all other dimensions remain the same.

example

M = mean(A,dim) returns the mean along dimension dim. For example, if A is a matrix, then mean(A,2) is a column vector containing the mean of each row.

example

M = mean(___,outtype) returns the mean with a specified data type, using any of the input arguments in the previous syntaxes. outtype can be 'default', 'double', or 'native'.

example

M = mean(___,nanflag) specifies whether to include or omit NaN values from the calculation for any of the previous syntaxes. mean(A,'includenan') includes all NaN values in the calculation while mean(A,'omitnan') ignores them.

Examples

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Mean of Matrix Columns

Create a matrix and compute the mean of each column.

A = [0 1 1; 2 3 2; 1 3 2; 4 2 2]
A =

     0     1     1
     2     3     2
     1     3     2
     4     2     2

M = mean(A)
M =

    1.7500    2.2500    1.7500

Mean of Matrix Rows

Create a matrix and compute the mean of each row.

A = [0 1 1; 2 3 2]
A =

     0     1     1
     2     3     2

M = mean(A,2)
M =

    0.6667
    2.3333

Mean of 3-D Array

Create a 4-by-2-by-3 array of integers between 1 and 10 and compute the mean values along the second dimension.

A = gallery('integerdata',10,[4,2,3],1);
M = mean(A,2)
M(:,:,1) =

    9.5000
    6.5000
    9.5000
    6.0000


M(:,:,2) =

    1.5000
    4.0000
    7.5000
    7.5000


M(:,:,3) =

    7.0000
    2.5000
    4.0000
    5.5000

Mean of Single-Precision Array

Create a single-precision vector of ones and compute its single-precision mean.

A = single(ones(1e8,1));
M = mean(A,'native')
M =

     1

The expected mean, 1, cannot be represented in single-precision due to saturation. Use the double output type to calculate the expected mean of A.

M = mean(A,'double')
M =

     1

Mean Excluding NaN

Create a vector and compute its mean, excluding NaN values.

A = [1 0 0 1 NaN 1 NaN 0];
M = mean(A,'omitnan')
M =

    0.5000

If you do not specify 'omitnan', then mean(A) returns NaN.

Input Arguments

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A — Input arrayvector | matrix | multidimensional array

Input array, specified as a vector, matrix, or multidimensional array.

  • If A is a scalar, then mean(A) returns A.

  • If A is an empty 0-by-0 matrix, then mean(A) returns NaN.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char | datetime | duration

dim — Dimension to operate alongpositive integer scalar

Dimension to operate along, specified as a positive integer scalar. If no value is specified, then the default is the first array dimension whose size does not equal 1.

Dimension dim indicates the dimension whose length reduces to 1. The size(M,dim) is 1, while the sizes of all other dimensions remain the same.

Consider a two-dimensional input array, A.

  • If dim = 1, then mean(A,1) returns a row vector containing the mean of the elements in each column.

  • If dim = 2, then mean(A,2) returns a column vector containing the mean of the elements in each row.

mean returns A when dim is greater than ndims(A) or when size(A,dim) is 1.

Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

outtype — Output data type'default' (default) | 'double' | 'native'

Output data type, specified as 'default', 'double', or 'native'. These options also specify the data type in which the operation is performed.

outtypeOutput data type
'default'double, unless the input data type is single, duration, or datetime, in which case, the output is 'native'
'double'double, unless the data type is duration or datetime, in which case, 'double' is not supported
'native'same data type as the input, unless
  • Input data type is logical, in which case, the output is double

  • Input data type is char, in which case, 'native'is not supported

Data Types: char

nanflagNaN conditionincludenan' (default) | ‘omitnan'

NaN condition, specified as one of these values:

  • 'includenan' — Include NaN values when computing the mean, resulting in NaN.

  • 'omitnan' — Ignore all NaN values in the input.

The mean function does not support the nanflag option for datetime or duration arrays.

Data Types: char

More About

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Mean

For a random variable vector A made up of N scalar observations, the mean is defined as

μ=1Ni=1NAi.

See Also

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