Bivariate Moment

BivariateMoment(int r, int s, int[] calldata p, int[] calldata q, int[] calldata weights, uint8 precision) returns the weighted mixed moment between the samples x and y.

$$E[(x - μ_x)^r*(y - μ_y)^s]$$

Lenght of p and q and weights must be equal. Precision representes the number of decimal places between 0 and 18. It is applied to r,s,p,q, weights and the output.

function BivariateMoment(int r, int s, int[] calldata p, int[] calldata q, int[] calldata weights, uint8 precision) external returns (int)

Under the hood, the following functions are utilized directly in the Neural client.

func (con *NeuralMath) BivariateMoment(gas *big.Int, r, s *big.Int, p, q, weights []*big.Int, precision uint8) (*big.Int, error, *big.Int) {
	mul, err := validatePrecision(precision)
	if err != nil {
		return nil, err, nil
	}
	if len(p) != len(q) {
		return nil, errors.New("p must have the same length as q"), nil
	}
	if len(p) != len(weights) {
		return nil, errors.New("p must have the same length as weights"), nil
	}

	rf, err := toFloat(r, mul)
	if err != nil {
		return nil, err, nil
	}
	sf, err := toFloat(r, mul)
	if err != nil {
		return nil, err, nil
	}
	pf, err := toFloats(p, mul)
	if err != nil {
		return nil, err, nil
	}
	qf, err := toFloats(q, mul)
	if err != nil {
		return nil, err, nil
	}
	wf, err := toFloats(weights, mul)
	if err != nil {
		return nil, err, nil
	}
	moment := stat.BivariateMoment(rf, sf, pf, qf, wf)
	return toBig(moment, mul), nil, nil
}