whats the meaning of DIM Std ?
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std
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std
Standard deviation
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Syntax
S = std(A)
S = std(A,w)
S = std(A,w,dim)
S = std(___,nanflag)
Description
example
S = std(A) returns the standard deviation of the elements of A along the first array dimension whose size does not equal 1.
If A is a vector of observations, then the standard deviation is a scalar.
If A is a matrix whose columns are random variables and whose rows are observations, then S is a row vector containing the standard deviations corresponding to each column.
If A is a multidimensional array, then std(A) operates along the first array dimension whose size does not equal 1, treating the elements as vectors. The size of this dimension becomes 1while the sizes of all other dimensions remain the same.
By default, the standard deviation is normalized by N-1, where N is the number of observations.
example
S = std(A,w) specifies a weighting scheme for any of the previous syntaxes. When w = 0 (default), S is normalized by N-1. When w = 1, S is normalized by the number of observations, N. w also can be a weight vector containing nonnegative elements. In this case, the length of wmust equal the length of the dimension over which std is operating.
example
S = std(A,w,dim) returns the standard deviation along dimension dim for any of the previous syntaxes. To maintain the default normalization while specifying the dimension of operation, set w = 0 in the second argument.
example
S = std(___,nanflag) specifies whether to include or omit NaN values from the calculation for any of the previous syntaxes. For example, std(A,'includenan') includes all NaNvalues in A while std(A,'omitnan')ignores them.
Examples
collapse all
Standard Deviation of Matrix Columns
Try it in MATLAB
Create a matrix and compute the standard deviation of each column.
A = [4 -5 1; 2 3 5; -9 1 7]; S = std(A)
S = 1×3 7.0000 4.1633 3.0551
Standard Deviation of 3-D Array
Try it in MATLAB
Create a 3-D array and compute the standard deviation along the first dimension.
A(:,:,1) = [2 4; -2 1]; A(:,:,2) = [9 13; -5 7]; A(:,:,3) = [4 4; 8 -3]; S = std(A)
S = S(:,:,1) = 2.8284 2.1213 S(:,:,2) = 9.8995 4.2426 S(:,:,3) = 2.8284 4.9497
Specify Standard Deviation Weights
Try it in MATLAB
Create a matrix and compute the standard deviation of each column according to a weight vector w.
A = [1 5; 3 7; -9 2]; w = [1 1 0.5]; S = std(A,w)
S = 1×2 4.4900 1.8330
Standard Deviation Along Matrix Rows
Try it in MATLAB
Create a matrix and calculate the standard deviation along each row.
A = [6 4 23 -3; 9 -10 4 11; 2 8 -5 1]; S = std(A,0,2)
S = 3×1 11.0303 9.4692 5.3229
Standard Deviation Excluding NaN
Try it in MATLAB
Create a vector and compute its standard deviation, excluding NaNvalues.
A = [1.77 -0.005 3.98 -2.95 NaN 0.34 NaN 0.19]; S = std(A,'omitnan')
S = 2.2797
Input Arguments
collapse all
A — Input array
vector | matrix | multidimensional array
Input array, specified as a vector, matrix, or multidimensional array. If A is a scalar, then std(A) returns 0. If A is a 0-by-0 empty array, then std(A) returns NaN.
Data Types: single | double | datetime | duration
Complex Number Support: Yes
w — Weight
0 (default) | 1 | vector
Weight, specified as one of these values:
0 — Normalize by N-1, where N is the number of observations. If there is only one observation, then the weight is 1.
1 — Normalize by N.
Vector made up of nonnegative scalar weights corresponding to the dimension of A along which the standard deviation is calculated.
Data Types: single | double
dim — Dimension to operate along
positive 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(S,dim) is 1, while the sizes of all other dimensions remain the same.
Consider a two-dimensional input array, A.
If dim = 1, then std(A,0,1) returns a row vector containing the standard deviation of the elements in each column.

If dim = 2, then std(A,0,2) returns a column vector containing the standard deviation of the elements in each row.

If dim is greater than ndims(A), then std(A)returns an array of zeros the same size as A.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
nanflag — NaN condition
'includenan' (default) | 'omitnan'
NaN condition, specified as one of these values:
'includenan' — Include NaN values when computing the standard deviation, resulting in NaN.
'omitnan' — Ignore NaN values appearing in either the input array or weight vector
Search MATLAB Documentation
Documentation
Toggle navigation
Documentation Home
MATLAB
Data Import and Analysis
Descriptive Statistics
MATLAB
Functions
std
ON THIS PAGE
Syntax
Description
Examples
Input Arguments
More About
Extended Capabilities
See Also
std
Standard deviation
collapse all in page
Syntax
S = std(A)
S = std(A,w)
S = std(A,w,dim)
S = std(___,nanflag)
Description
example
S = std(A) returns the standard deviation of the elements of A along the first array dimension whose size does not equal 1.
If A is a vector of observations, then the standard deviation is a scalar.
If A is a matrix whose columns are random variables and whose rows are observations, then S is a row vector containing the standard deviations corresponding to each column.
If A is a multidimensional array, then std(A) operates along the first array dimension whose size does not equal 1, treating the elements as vectors. The size of this dimension becomes 1while the sizes of all other dimensions remain the same.
By default, the standard deviation is normalized by N-1, where N is the number of observations.
example
S = std(A,w) specifies a weighting scheme for any of the previous syntaxes. When w = 0 (default), S is normalized by N-1. When w = 1, S is normalized by the number of observations, N. w also can be a weight vector containing nonnegative elements. In this case, the length of wmust equal the length of the dimension over which std is operating.
example
S = std(A,w,dim) returns the standard deviation along dimension dim for any of the previous syntaxes. To maintain the default normalization while specifying the dimension of operation, set w = 0 in the second argument.
example
S = std(___,nanflag) specifies whether to include or omit NaN values from the calculation for any of the previous syntaxes. For example, std(A,'includenan') includes all NaNvalues in A while std(A,'omitnan')ignores them.
Examples
collapse all
Standard Deviation of Matrix Columns
Try it in MATLAB
Create a matrix and compute the standard deviation of each column.
A = [4 -5 1; 2 3 5; -9 1 7]; S = std(A)
S = 1×3 7.0000 4.1633 3.0551
Standard Deviation of 3-D Array
Try it in MATLAB
Create a 3-D array and compute the standard deviation along the first dimension.
A(:,:,1) = [2 4; -2 1]; A(:,:,2) = [9 13; -5 7]; A(:,:,3) = [4 4; 8 -3]; S = std(A)
S = S(:,:,1) = 2.8284 2.1213 S(:,:,2) = 9.8995 4.2426 S(:,:,3) = 2.8284 4.9497
Specify Standard Deviation Weights
Try it in MATLAB
Create a matrix and compute the standard deviation of each column according to a weight vector w.
A = [1 5; 3 7; -9 2]; w = [1 1 0.5]; S = std(A,w)
S = 1×2 4.4900 1.8330
Standard Deviation Along Matrix Rows
Try it in MATLAB
Create a matrix and calculate the standard deviation along each row.
A = [6 4 23 -3; 9 -10 4 11; 2 8 -5 1]; S = std(A,0,2)
S = 3×1 11.0303 9.4692 5.3229
Standard Deviation Excluding NaN
Try it in MATLAB
Create a vector and compute its standard deviation, excluding NaNvalues.
A = [1.77 -0.005 3.98 -2.95 NaN 0.34 NaN 0.19]; S = std(A,'omitnan')
S = 2.2797
Input Arguments
collapse all
A — Input array
vector | matrix | multidimensional array
Input array, specified as a vector, matrix, or multidimensional array. If A is a scalar, then std(A) returns 0. If A is a 0-by-0 empty array, then std(A) returns NaN.
Data Types: single | double | datetime | duration
Complex Number Support: Yes
w — Weight
0 (default) | 1 | vector
Weight, specified as one of these values:
0 — Normalize by N-1, where N is the number of observations. If there is only one observation, then the weight is 1.
1 — Normalize by N.
Vector made up of nonnegative scalar weights corresponding to the dimension of A along which the standard deviation is calculated.
Data Types: single | double
dim — Dimension to operate along
positive 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(S,dim) is 1, while the sizes of all other dimensions remain the same.
Consider a two-dimensional input array, A.
If dim = 1, then std(A,0,1) returns a row vector containing the standard deviation of the elements in each column.

If dim = 2, then std(A,0,2) returns a column vector containing the standard deviation of the elements in each row.

If dim is greater than ndims(A), then std(A)returns an array of zeros the same size as A.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
nanflag — NaN condition
'includenan' (default) | 'omitnan'
NaN condition, specified as one of these values:
'includenan' — Include NaN values when computing the standard deviation, resulting in NaN.
'omitnan' — Ignore NaN values appearing in either the input array or weight vector
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