function standardize( N, X, strideX, offsetX, mean, strideM, offsetM, stdev, strideS, offsetS ) { // eslint-disable-line max-len
	var xi;
	var mi;
	var si;
	var i;

	// TODO: consider moving to an "extended" BLAS package

	xi = offsetX;
	mi = offsetM;
	si = offsetS;
	for ( i = 0; i < N; i++ ) {
		X[ xi ] = ( X[ xi ] - mean[ mi ] ) / stdev[ si ];
		xi += strideX;
		mi += strideM;
		si += strideS;
	}
	return X;
}
Normalizes a vector by standardization.

@private
@param {NonNegativeInteger} N - number of elements
@param {NumericArray} X - strided array
@param {integer} strideX - stride
@param {NonNegativeInteger} offsetX - index offset
@param {NumericArray} mean - strided array containing the sample mean along each dimension
@param {integer} strideM - stride
@param {NonNegativeInteger} offsetM - index offset
@param {NumericArray} stdev - strided array containing the standard deviation along each dimension
@param {integer} strideS - stride
@param {NonNegativeInteger} offsetS - index offset
@returns {ndarray} input array