Fit RS generalised lambda distribution to data set using L moment matching
This function fits RS generalised lambda distribution to data set using L moment matching
fun.RPRS.lm(data, rs.init = c(-1.5, 1.5), leap = 3, FUN = "runif.sobol", no = 10000)
data |
Dataset to be fitted |
rs.init |
Initial values for RS 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 L moment fitting scheme for RS 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 RS 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 parameters of the RS generalised lambda distribution.
Steve Su
Asquith, W. (2007). "L-moments and TL-moments of the generalized lambda distribution." Computational Statistics and Data Analysis 51(9): 4484-4496.
Karvanen, J. and A. Nuutinen (2008). "Characterizing the generalized lambda distribution by L-moments." Computational Statistics and Data Analysis 52(4): 1971-1983.
## Fitting the normal distribution # fun.RPRS.lm(data=rnorm(1000,2,3),rs.init=c(-1.5,1.5),leap=3)
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