Hi everyone, I've added the ability to handle weighted data in a covariance calculation, in a similar manner to that already implemented for the calculation of a weighted average. https://github.com/tpoole/numpy/compare/weighted_cov Could an experienced someone please look over my changes before I submit a pull request? Validation of the formula can be found at "Exponential smoothing weighted correlations", F. Pozzi, T. Matteo, and T. Aste, Eur. Phys. J. B. 85, 175 (2012). --- though it is unfortunately paywalled and "An Analysis of WinCross, SPSS, and Mentor Procedures for Estimating the Variance of a Weighted Mean", A. Madansky and H. G. B. Alexander, www.analyticalgroup.com/download/weighted_variance.pdf for the "effective number of samples". Thanks, Tom -- View this message in context: http://numpy-discussion.10968.n7.nabble.com/Requesting-Code-Review-of-weight... Sent from the Numpy-discussion mailing list archive at Nabble.com.