Compute the standard deviation of the elements of the vector x.
The standard deviation is defined as
std (x) = sqrt ( 1/(N-1) SUM_i (x(i) - mean(x))^2 )
where N is the number of elements.
If x is a matrix, compute the standard deviation for each column and return them in a row vector.
The argument opt determines the type of normalization to use. Valid values are
normalize with N-1, provides the square root of the best unbiased estimator of the variance [default]
normalize with N, this provides the square root of the second moment around the mean
If the optional argument dim is given, operate along this dimension.
See also: var, range, iqr, mean, median.
Package: octave