nigFitStart {GeneralizedHyperbolic} | R Documentation |
Find Starting Values for Fitting a normal inverse Gaussian Distribution
Description
Finds starting values for input to a maximum likelihood routine for fitting normal inverse Gaussian distribution to data.
Usage
nigFitStart(x, startValues = c("FN","Cauchy","MoM","US"),
paramStart = NULL,
startMethodMoM = c("Nelder-Mead","BFGS"), ...)
nigFitStartMoM(x, startMethodMoM = "Nelder-Mead", ...)
Arguments
x |
data vector. |
startValues |
a |
paramStart |
starting values for param if |
startMethodMoM |
Method used by call to |
... |
Details
Possible values of the argument startValues
are the following:
"US"
User-supplied.
"FN"
A fitted normal distribution.
"Cauchy"
Based on a fitted Cauchy distribution, from
fitdistr()
of the MASS package."MoM"
Method of moments.
If startValues = "US"
then a value must be supplied for
paramStart
.
If startValues = "MoM"
, nigFitStartMoM
is
called. If startValues = "MoM"
an initial
optimisation is needed to find the starting values. These
optimisations call optim
.
Value
nigFitStart
returns a list with components:
paramStart |
A vector with elements |
xName |
A character string with the actual |
breaks |
The cell boundaries found by a call to
|
midpoints |
The cell midpoints found by a call to
|
empDens |
The estimated density found by a call to
|
nigFitStartMoM
returns only the method of moments estimates
as a vector with elements mu
, delta
, alpha
and
beta
.
Author(s)
David Scott d.scott@auckland.ac.nz, Christine Yang Dong
References
Barndorff-Nielsen, O. (1977) Exponentially decreasing distributions for the logarithm of particle size, Proc. Roy. Soc. Lond., A353, 401–419.
Barndorff-Nielsen, O., Blæsild, P., Jensen, J., and Sörenson, M. (1985). The fascination of sand. In A celebration of statistics, The ISI Centenary Volume, eds., Atkinson, A. C. and Fienberg, S. E., pp. 57–87. New York: Springer-Verlag.
Fieller, N. J., Flenley, E. C. and Olbricht, W. (1992) Statistics of particle size data. Appl. Statist., 41, 127–146.
See Also
dnig
, dskewlap
,
nigFit
, hist
, optim
,
fitdistr
.
Examples
param <- c(2, 2, 2, 1)
dataVector <- rnig(500, param = param)
nigFitStart(dataVector, startValues = "FN")
nigFitStartMoM(dataVector)
nigFitStart(dataVector, startValues = "MoM")