| ghyp-get | R Documentation |
These functions simply return data stored within generalized
hyperbolic distribution objects, i.e. slots of the classes ghyp
and mle.ghyp. ghyp.fit.info extracts information about
the fitting procedure from objects of class
mle.ghyp. ghyp.data returns the
data slot of a gyhp object. ghyp.dim returns the
dimension of a gyhp object. ghyp.name returns the
name of the distribution of a gyhp object.
ghyp.fit.info(object)
ghyp.data(object)
ghyp.name(object, abbr = FALSE, skew.attr = TRUE)
ghyp.dim(object)
object |
An object inheriting from class
|
abbr |
If |
skew.attr |
If |
ghyp.fit.info returns list with components:
logLikelihood | The maximized log-likelihood value. |
aic | The Akaike information criterion. |
fitted.params | A boolean vector stating which parameters were fitted. |
converged | A boolean whether optim converged or not. |
n.iter | The number of iterations. |
error.code | Error code from optim. |
error.message | Error message from optim. |
parameter.variance | Parameter variance (only for univariate fits). |
trace.pars | Trace values of the parameters during the fitting procedure. |
ghyp.data returns NULL if no data is stored within the
object, a vector if it is an univariate generalized hyperbolic
distribution and matrix if it is an multivariate generalized
hyperbolic distribution.
ghyp.name returns the name of the ghyp distribution which can be the name of a special case.
Depending on the arguments abbr and skew.attr one of the following is returned.
abbr == FALSE & skew.attr == TRUE | abbr == TRUE & skew.attr == TRUE |
| (A)symmetric Generalized Hyperbolic | (A)symm ghyp |
| (A)symmetric Hyperbolic | (A)symm hyp |
| (A)symmetric Normal Inverse Gaussian | (A)symm NIG |
| (A)symmetric Variance Gamma | (A)symm VG |
| (A)symmetric Student-t | (A)symm t |
| Gaussian | Gauss |
abbr == FALSE & skew.attr == FALSE | abbr == TRUE & skew.attr == FALSE |
| Generalized Hyperbolic | ghyp |
| Hyperbolic | hyp |
| Normal Inverse Gaussian | NIG |
| Variance Gamma | VG |
| Student-t | t |
| Gaussian | Gauss |
ghyp.dim returns the dimension of a ghyp object.
ghyp.fit.info requires an object of class
mle.ghyp. In the univariate case the
parameter variance is returned as well. The parameter variance is
defined as the inverse of the negative hesse-matrix computed by
optim. Note that this makes sense only in the case that
the estimates are asymptotically normal distributed.
The class ghyp contains a data slot.
Data can be stored either when an object is initialized or via the
fitting routines and the argument save.data.
David Luethi
coef, mean, vcov,
logLik, AIC for other accessor functions,
fit.ghypmv, fit.ghypuv, ghyp for constructor functions,
optim for possible error messages.
## multivariate generalized hyperbolic distribution
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 data
ghyp.data(ghyp.mv)
## Get the dimension
ghyp.dim(ghyp.mv)
## Get the name of the ghyp object
ghyp.name(ghyp(alpha.bar = 0))
ghyp.name(ghyp(alpha.bar = 0, lambda = -4), abbr = TRUE)
## 'ghyp.fit.info' does only work when the object is of class 'mle.ghyp',
## i.e. is created by 'fit.ghypuv' etc.
mv.fit <- fit.tmv(data = ghyp.data(ghyp.mv), control = list(abs.tol = 1e-3))
ghyp.fit.info(mv.fit)
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