Performs Welford's online algorithm for updating correlation. While it only iterates each input once, it can be slower for smaller inputs. However, it is also more accurate. Can also put another CorrelationAccumulator of the same type, which uses the parallel algorithm from Chan et al.

Calculates correlation using (E(x*y) - E(x)*E(y))/(sqrt(E(x^2)-E(x)^2)*sqrt(E(y^2)-E(y)^2)) (alowing for adjustments for population/sample variance). This algorithm can be numerically unstable.

Calculates correlation using a two-pass algorithm whereby the inputs are first centered and then the sum of products is calculated from that. May be faster than online and generally more accurate than the naive algorithm.

Calculates correlation assuming the mean of the inputs is zero.

Calculates correlation assuming the mean of the inputs is zero and standard deviation is one.

When slices, slice-like objects, or ranges are the inputs, uses the two-pass algorithm. When an individual data-point is added, uses the online algorithm.