Estimates the distributional parameters for a generalized hyperbolic Student-t distribution.
ghtFit(x, beta = 0.1, delta = 1, mu = 0, nu = 10,
scale = TRUE, doplot = TRUE, span = "auto", trace = TRUE,
title = NULL, description = NULL, ...)an object from class "fDISTFIT".
Slot fit is a list, currently with components
estimate, minimum and code.
numeric values.
beta is the skewness parameter in the range (0, alpha);
delta is the scale parameter, must be zero or positive;
mu is the location parameter, by default 0.
These are the parameters in the first parameterization.
defines the number of degrees of freedom.
Note, alpha takes the limit of abs(beta),
and lambda=-nu/2.
a numeric vector.
a logical flag, by default TRUE. Should the time series
be scaled by its standard deviation to achieve a more stable
optimization?
a logical flag. Should a plot be displayed?
x-coordinates for the plot, by default 100 values
automatically selected and ranging between the 0.001,
and 0.999 quantiles. Alternatively, you can specify
the range by an expression like span=seq(min, max,
times = n), where, min and max are the
left and right endpoints of the range, and n gives
the number of the intermediate points.
a logical flag. Should the parameter estimation process be traced?
a character string which allows for a project title.
a character string which allows for a brief description.
parameters to be parsed.
The function nlm is used to minimize the "negative"
log-likelihood function. nlm carries out a minimization
using a Newton-type algorithm.
## ghtFit -
# Simulate Random Variates:
set.seed(1953)
## ghtFit -
# Fit Parameters:
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