Multivariate Pattern Analysis in Python

# mvpa2.misc.dcov.dCOV

`mvpa2.misc.dcov.``dCOV`(x, y, rowvar=1, uv=False, all_est=True)

  Estimate dCov measure(s) between x and y. Allows uni- or multi-variate estimations

  Name dCOV was chosen to match implementation in R energy toolbox: http://cran.r-project.org/web/packages/energy/index.html

  Parameters:

  rowvar : int, optional

  > If `rowvar` is 1 (default), then each row represents a variable, with observations in the columns. If 0, the relationship is transposed: each column represents a variable, while the rows contain observations.

  uv : bool, optional

  > dCov is a multivariate measure of dependence so it would produce a single estimate for two matrices NxT and MxT. With uv=True (univariate estimation) it will return estimates for every pair of variables from x and y, thus NxM matrix, somewhat similar to what numpy.corrcoef does besides not estimating within x or y

  all_est : bool, True

  > Since majority of computation of dCor(x,y), dVar(x) and dVar(y) is spend while estimating dVar(x, y) it makes sense to estimate all of them at the same time if any of the later is necessary. So output would then consist of dCov, dCor, dVar(x), dVar(y) tuple, matching the order of energy toolbox dCOV output in R.