wdm

wdm(x: numpy.ndarray, y: numpy.ndarray, method: str, weights: numpy.ndarray = array([], dtype=float64), remove_missing: bool = True) → float

Calculates (weighted) dependence measures.

This function computes various measures of dependence between two variables, optionally using observation weights.

Parameters:

x, y

Input data vectors.

method

The dependence measure to compute. Possible values are:

• "pearson", "prho", "cor" : Pearson correlation

• "spearman", "srho", "rho" : Spearman’s \(\rho\)

• "kendall", "ktau", "tau" : Kendall’s \(\tau\)

• "blomqvist", "bbeta", "beta" : Blomqvist’s \(\beta\)

• "hoeffding", "hoeffd", "d" : Hoeffding’s \(D\)

weights

Optional vector of observation weights.

remove_missing

If True, all observations containing a NaN are removed. Otherwise, an error is raised if missing values are present.

Returns:

float

The computed dependence measure.