Estimates the distrinbutional parameters for a standardized generalized hyperbolic distribution.
sghFit(x, zeta = 1, rho = 0, lambda = 1, include.lambda = TRUE, scale = TRUE, doplot = TRUE, span = "auto", trace = TRUE, title = NULL, description = NULL, ...)
zeta
is positive,
skewness parameter rho
is in the range (-1, 1).
and index parameter lambda
, by default 1.
TRUE
. Should the index
parameter lambda
included in the parameter estimate?
TRUE
. Should the time series
be scaled by its standard deviation to achieve a more stable
optimization?
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.
estimate
.
Either estimate
is an approximate local minimum of the
function or steptol
is too small;
4: iteration limit exceeded;
5: maximum step size stepmax
exceeded five consecutive times.
Either the function is unbounded below, becomes asymptotic to a
finite value from above in some direction or stepmax
is too small.
## sghFit -
# Simulate Random Variates:
set.seed(1953)
s = rsgh(n = 2000, zeta = 0.7, rho = 0.5, lambda = 0)
## sghFit -
# Fit Parameters:
sghFit(s, zeta = 1, rho = 0, lambda = 1, include.lambda = TRUE,
doplot = TRUE)
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