AsymVarMaxLinear: Asymptotic variance matrix for the max-linear model.

In tailDepFun: Minimum Distance Estimation of Tail Dependence Models

Description

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

Usage

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.

Value

A q by q matrix.

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

Examples

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

tailDepFun documentation built on June 3, 2021, 5:10 p.m.