AsymVarMaxLinear function

Asymptotic variance matrix for the max-linear model.

Computes the asymptotic variance matrix for the max-linear model, estimated using the weighted least squares estimator.

AsymVarMaxLinear(indices, par, Bmatrix = NULL)

Arguments

• indices: A $q$ x $d$ matrix containing at least 2 non-zero elements per row, representing the values in which we will evaluate the stable tail dependence function.
• par: The parameter vector.
• Bmatrix: A function that converts the parameter vector theta to a parameter matrix B. If NULL, then a simple 2-factor model is assumed.

Returns

A q by q matrix.

Examples

indices <- selectGrid(c(0,0.5,1), d = 3, nonzero = 3)
AsymVarMaxLinear(indices, par = c(0.1,0.55,0.75))

References

Einmahl, J.H.J., Kiriliouk, A., and Segers, J. (2018). A continuous updating weighted least squares estimator of tail dependence in high dimensions. Extremes 21(2), 205-233.

See Also

selectGrid