Revision 50e63163d97a24ea4258d0434c6206f5e748a9c6 authored by Yohan Chalabi on 21 September 2012, 00:00:00 UTC, committed by Gabor Csardi on 21 September 2012, 00:00:00 UTC
1 parent e45edf4
dist-snigFit.Rd
\name{snigFit}
\alias{snigFit}
\title{Fit of a Stndardized NIG Distribution}
\description{
Estimates the parameters of a standardized normal inverse
Gaussian distribution.
}
\usage{
snigFit(x, zeta = 1, rho = 0, scale = TRUE, doplot = TRUE,
span = "auto", trace = TRUE, title = NULL, description = NULL, \dots)
}
\arguments{
\item{zeta, rho}{
shape parameter \code{zeta} is positive,
skewness parameter \code{rho} is in the range (-1, 1).
}
\item{description}{
a character string which allows for a brief description.
}
\item{doplot}{
a logical flag. Should a plot be displayed?
}
\item{scale}{
a logical flag, by default \code{TRUE}. Should the time series
be scaled by its standard deviation to achieve a more stable
optimization?
}
\item{span}{
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 \code{span=seq(min, max,
times = n)}, where, \code{min} and \code{max} are the
left and right endpoints of the range, and \code{n} gives
the number of the intermediate points.
}
\item{title}{
a character string which allows for a project title.
}
\item{trace}{
a logical flag. Should the parameter estimation process be
traced?
}
\item{x}{
a numeric vector.
}
\item{\dots}{
parameters to be parsed.
}
}
\value{
The function \code{snigFit} returns a list with the following
components:
\item{estimate}{
the point at which the maximum value of the log liklihood
function is obtained.
}
\item{minimum}{
the value of the estimated maximum, i.e. the value of the
log liklihood function.
}
\item{code}{
an integer indicating why the optimization process terminated.\cr
1: relative gradient is close to zero, current iterate is probably
solution; \cr
2: successive iterates within tolerance, current iterate is probably
solution; \cr
3: last global step failed to locate a point lower than \code{estimate}.
Either \code{estimate} is an approximate local minimum of the
function or \code{steptol} is too small; \cr
4: iteration limit exceeded; \cr
5: maximum step size \code{stepmax} exceeded five consecutive times.
Either the function is unbounded below, becomes asymptotic to a
finite value from above in some direction or \code{stepmax}
is too small.
}
\item{gradient}{
the gradient at the estimated maximum.
}
\item{steps}{
number of function calls.
}
}
\examples{
## snigFit -
# Simulate Random Variates:
set.seed(1953)
s = rsnig(n = 2000, zeta = 0.7, rho = 0.5)
## snigFit -
# Fit Parameters:
snigFit(s, zeta = 1, rho = 0, doplot = TRUE)
}
\keyword{distribution}
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