Fit FMKL generalised lambda distribution to data set using moment matching
This function fits FMKL generalised lambda distribution to data set using moment matching
fun.RMFMKL.mm(data, fmkl.init = c(-0.25, 1.5), leap = 3, FUN = "runif.sobol", no = 10000)
data |
Dataset to be fitted |
fmkl.init |
Initial values for FMKL distribution optimization,
|
leap |
Scrambling (0,1,2,3) for the Sobol sequence for the distribution
fit. See scrambling/leap argument for |
FUN |
A character string of either |
no |
Number of initial random values to find the best initial values for optimisation. |
This function provides method of moment fitting scheme for FMKL GLD. Note this function can fail if there are no defined percentiles from the data set or if the initial values do not lead to a valid FMKL generalised lambda distribution.
This function is based on scheme detailed in the literature below but it has been modified by the author (Steve Su).
A vector representing four parametefmkl of the FMKL generalised lambda distribution.
Steve Su
Karian, Z. and E. Dudewicz (2000). Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalised Bootstrap Methods. New York, Chapman and Hall.
## Fitting the normal distribution # fun.RMFMKL.mm(data=rnorm(1000,2,3),fmkl.init=c(-0.25,1.5),leap=3)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.