Fit RS generalised lambda distribution to data set using maximum likelihood estimation
This function fits RS generalised lambda distribution to data set using maximum likelihood estimation.
fun.RPRS.ml(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 one of the definitive fit to data set using generalised lambda distributions. 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.
A vector representing four parameters of the RS generalised lambda distribution.
Steve Su
Su, S. (2007). Numerical Maximum Log Likelihood Estimation for Generalized Lambda Distributions. Computational statistics and data analysis 51(8) 3983-3998.
Su (2007). Fitting Single and Mixture of Generalized Lambda Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R. Journal of Statistical Software: *21* 9.
## Fitting the normal distribution # fun.RPRS.ml(data=rnorm(1000,2,3),rs.init=c(-1.5,1.5),leap=3)
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