mle.ghypmv-class {ghyp}R Documentation

Class mle.ghypmv

Description

The class “mle.ghypmv” inherits from the class “ghypmv”. In addition to the class “ghypmv” this class stores fitting information. Namely the number of iterations n.iter, the log likelihood value llh, the Akaike Information Criterion aic, a boolean vector stating which parameters were fitted fitted.params, a boolean converged whether the fitting procedure converged or not, an error.code which stores the status of a possible error and the corresponding error.message

Objects from the Class

Objects should only be created by calls to the fitting routines like fit.ghypmv, fit.hypmv, fit.NIGmv , fit.VGmv and fit.tmv .

Slots

lambda:
Shape parameter of class "numeric".
alpha.bar:
Shape parameter of class "numeric".
chi:
Shape parameter of an alternative parametrization. Object of class "numeric".
psi:
Shape parameter of an alternative parametrization. Object of class "numeric".
mu:
Location parameter of lass "numeric".
sigma:
Dispersion parameter of class "matrix".
gamma:
Skewness parameter of class "numeric".
model:
Model, i.e., (a)symmetric generalized hyperbolic distribution or (a)symmetric special case. Object of class "character".
dimension:
Dimension of the generalized hyperbolic distribution. Object of class "numeric".
expected.value:
The expected value of a generalized hyperbolic distribution. Object of class "numeric".
variance:
The expected value of a generalized hyperbolic distribution. Object of class "matrix".
data:
Data matrix of class "matrix". When an object of class ghypmv is instantiated the user can decide whether data should be stored within the object or not. This may be useful when fitting eneralized hyperbolic distributions to data and perform further analysis afterwards.
n.iter:
The number of iterations of class "numeric".
llh:
The log likelihood value of class "numeric".
converged:
A boolean whether converged or not. Object of class "logical".
error.code:
An error code of class "numeric".
error.message:
An error message of class "character".
fitted.params:
A boolean vector stating which parameters were fitted of class "logical".
aic:
The value of the Akaike Information Criterion of class "numeric".

Extends

Class "ghypmv", directly. Class "ghypbase", by class "ghypmv", distance 2.

Methods

A “pairs” method (see pairs).
A “mean” method (see mean).
A “vcov” method (see vcov).

Note

When showing special cases of the generalized hyperbolic distribution the corresponding fixed parameters are plotted in brackets.

Author(s)

David Lüthi

See Also

optim for an interpretation of error.code and error.message, fit.ghypmv where objects of class mle.ghypuv were created, ghypmv-class to have a look on the base class.

Examples

  data(smi.stocks)
  fit.ghypmv(data=smi.stocks,opt.pars=c(lambda=FALSE, alpha.bar=FALSE),lambda=2)

[Package ghyp version 0.9.0 Index]