dot-gauss_hermite_normal: Gauss-Hermite quadrature nodes and weights for N(0,1)...
In wARMASVp: Winsorized ARMA Estimation for Higher-Order Stochastic Volatility Models
.gauss_hermite_normal R Documentation
Gauss-Hermite quadrature nodes and weights for N(0,1) integration
Computes nodes z_i and weights w_i such that sum(w_i * f(z_i)) approximates E[f(Z)]
where Z ~ N(0,1). Uses the Golub-Welsch algorithm.
Description
Gauss-Hermite quadrature nodes and weights for N(0,1) integration
Computes nodes z_i and weights w_i such that sum(w_i * f(z_i)) approximates E[f(Z)]
where Z ~ N(0,1). Uses the Golub-Welsch algorithm.
Usage
.gauss_hermite_normal(n = 200L)
Arguments
n
Number of quadrature points (default 200)
Value
List with components nodes and weights
wARMASVp documentation built on May 15, 2026, 5:07 p.m.
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| .gauss_hermite_normal | R Documentation |
Gauss-Hermite quadrature nodes and weights for N(0,1) integration Computes nodes z_i and weights w_i such that sum(w_i * f(z_i)) approximates E[f(Z)] where Z ~ N(0,1). Uses the Golub-Welsch algorithm.
Description
Gauss-Hermite quadrature nodes and weights for N(0,1) integration Computes nodes z_i and weights w_i such that sum(w_i * f(z_i)) approximates E[f(Z)] where Z ~ N(0,1). Uses the Golub-Welsch algorithm.
Usage
.gauss_hermite_normal(n = 200L)
Arguments
n |
Number of quadrature points (default 200) |
Value
List with components nodes and weights
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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