Computes the raw moments of the generalised lambda distribution up to 4th order.
This function is of theoretical interest only.
fun.rawmoments(L1, L2, L3, L4, param = "fmkl")
L1 |
Location parameter of the generalised lambda distribution. |
L2 |
Scale parameter of the generalised lambda distribution. |
L3 |
First shape parameter of the generalised lambda distribution. |
L4 |
Second shape parameter of the generalised lambda distribution. |
param |
|
This function is the building block for fun.theo.bi.mv.gld.
A vector showing the raw moments of the specified generalised lambda distribution up to the fourth order.
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.
Karian, Zaven A. and Dudewicz, Edward J. (2000), Fitting statistical distributions: the Generalized Lambda Distribution and Generalized Bootstrap methods, Chapman & Hall
Ramberg, J. S. & Schmeiser, B. W. (1974), An approximate method for generating asymmetric random variables, Communications of the ACM *17*, 78-82.
~~objects to See Also as help, ~~~
## Generate some random numbers using FMKL and RS generalised lambda ## distributions and then compute the empirical and theoretical ## E(X), E(X^2), E(X^3), E(X^4) junk<-rgl(100000,1,2,3,4) mean(junk) mean(junk^2) mean(junk^3) mean(junk^4) junk<-rgl(100000,1,2,3,4,"rs") mean(junk) mean(junk^2) mean(junk^3) mean(junk^4) fun.rawmoments(1,2,3,4) fun.rawmoments(1,2,3,4,"rs")
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