Find the theoretical first four moments of the generalised lambda distribution.
Computes the "mean","variance","skewness","kurtosis" statistics from a given generalised lambda distribution.
fun.theo.mv.gld(L1, L2, L3, L4, param, normalise="N")
L1 |
Lambda 1. Or c(Lambda 1,Lambda 2,Lambda 3,Lambda 4). |
L2 |
Lambda 2. |
L3 |
Lambda 3. |
L4 |
Lambda 4. |
param |
"rs" or "fmkl" or "fkml" |
normalise |
"Y" if you want kurtosis to be calculated with reference to kurtosis = 0 under Normal distribution. |
A vector listing the values of mean, variance, skewness and kurtosis.
Sometimes the theoretical moments may not exist, in those cases,
NA is returned.
Steve Su
Freimer, M., Mudholkar, G. S., Kollia, G. & Lin, C. T. (1988), A study of the generalized tukey lambda family, Communications in Statistics - Theory and Methods *17*, 3547-3567.
Gilchrist, Warren G. (2000), Statistical Modelling with Quantile Functions, Chapman & Hall
Karian, Z.A., Dudewicz, E.J., and McDonald, P. (1996), The extended generalized lambda distribution system for fitting distributions to data: history, completion of theory, tables, applications, the “Final Word” on Moment fits, Communications in Statistics - Simulation and Computation *25*, 611-642.
Karian, Zaven A. and Dudewicz, Edward J. (2000), Fitting statistical distributions: the Generalized Lambda Distribution and Generalized Bootstrap methods, Chapman & Hall
fun.theo.mv.gld(1, 2, 3, 4, "rs") fun.theo.mv.gld(1, 2, 3, 4, "fmkl")
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