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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