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std(v[, region])

Compute the sample standard deviation of a vector or array v, optionally along dimensions in region. The algorithm returns an estimator of the generative distribution's standard deviation under the assumption that each entry of v is an IID drawn from that generative distribution. This computation is equivalent to calculating sqrt(sum((v - mean(v)).^2) / (length(v) - 1)). Note: Julia does not ignore NaN values in the computation. For applications requiring the handling of missing data, the DataArray package is recommended.

Examples

std(v[, region]) computes the sample standard deviation of a vector or array v, optionally along dimensions specified by region. The function returns an estimator of the generative distribution's standard deviation, assuming each entry of v is independently and identically distributed (IID) from that generative distribution.

The computation is equivalent to calculating sqrt(sum((v - mean(v)).^2) / (length(v) - 1)). It's important to note that Julia does not ignore NaN values in the computation.

Here are some examples of how to use the std function:

1. Compute the standard deviation of a vector:

   julia> v = [1, 2, 3, 4, 5];
   julia> std(v)
   1.5811388300841898

   This example calculates the standard deviation of the vector v.

2. Calculate the standard deviation along a specific dimension of an array:

   julia> A = [1 2 3; 4 5 6; 7 8 9];
   julia> std(A, 1)  # Calculate along the rows (dimension 1)
   3-element Array{Float64,1}:
   2.449489742783178
   2.449489742783178
   2.449489742783178

   In this example, the standard deviation is computed along the rows (dimension 1) of the 2-dimensional array A.

3. Compute the standard deviation of a subset of a vector:

   julia> v = [1, 2, 3, 4, 5];
   julia> std(v[2:end])
   1.5811388300841898

   Here, the standard deviation is calculated for a subset of the vector v excluding the first element.

Remember that std follows the Bessel's correction, dividing by (length(v) - 1) instead of length(v) to estimate the generative distribution's standard deviation accurately from the sample.

Note: If you need to handle missing data, the DataArray package is recommended.

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