Extract parameters of generalized hyperbolic distribution objects
The function coef
returns the parameters of a generalized
hyperbolic distribution object as a list. The user can choose between
the “chi/psi”, the “alpha.bar” and the
“alpha/delta” parametrization. The function coefficients
is a synonym for coef
.
## S4 method for signature 'ghyp' coef(object, type = c("chi.psi", "alpha.bar", "alpha.delta")) ## S4 method for signature 'ghyp' coefficients(object, type = c("chi.psi", "alpha.bar", "alpha.delta"))
object |
An object inheriting from class |
type |
According to |
Internally, the “chi/psi” parametrization is used. However, fitting is only possible in the “alpha.bar” parametrization as it provides the most convenient parameter constraints.
If type
is “chi.psi” a list with components:
lambda |
Shape parameter. |
chi |
Shape parameter. |
psi |
Shape parameters. |
mu |
Location parameter. |
sigma
|
Dispersion parameter. |
gamma
|
Skewness parameter. |
If type
is “alpha.bar” a list with components:
lambda |
Shape parameter. |
alpha.bar |
Shape parameter. |
mu |
Location parameter. |
sigma
|
Dispersion parameter. |
gamma
|
Skewness parameter. |
If type
is “alpha.delta” a list with components:
lambda |
Shape parameter. |
alpha |
Shape parameter. |
delta
|
Shape parameter. |
mu
|
Location parameter. |
Delta
|
Dispersion matrix with a determinant of 1 (only returned in the multivariate case). |
beta |
Shape and skewness parameter. |
A switch from either the “chi/psi” to the “alpha.bar” or from the “alpha/delta” to the “alpha.bar” parametrization is not yet possible.
David Luethi
ghyp.mv <- ghyp(lambda = 1, alpha.bar = 0.1, mu = rep(0,2), sigma = diag(rep(1,2)), gamma = rep(0,2), data = matrix(rt(1000, df = 4), ncol = 2)) ## Get parameters coef(ghyp.mv, type = "alpha.bar") coefficients(ghyp.mv, type = "chi.psi") ## Simple modification (do not modify slots directly e.g. object@mu <- 0:1) param <- coef(ghyp.mv, type = "alpha.bar") param$mu <- 0:1 do.call("ghyp", param) # returns a new 'ghyp' object
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