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.
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