Lcomoment.coefficients | R Documentation |
Compute the L-comoment coefficients from an L-comoment matrix of order k \ge 2
and the k = 2
(2nd order) L-comoment matrix. However, if the first argument is 1st-order then the coefficients of L-covariation are computed. The function requires that each matrix has already been computed by the function Lcomoment.matrix
.
Lcomoment.coefficients(Lk, L2)
Lk |
A |
L2 |
A |
The coefficient of L-variation is computed by Lcomoment.coefficients(L1,L2)
where L1
is a 1st-order L-moment matrix and L2
is a k = 2
L-comoment matrix. Symbolically, the coefficient of L-covariation is
\hat{\tau}_{[12]} = \frac{\hat{\lambda}_{2[12]}}
{\hat{\lambda}_{1[12]}} \mbox{.}
The higher L-comoment coefficients (L-coskew, L-cokurtosis, ...) are computed by the function Lcomoment.coefficients(L3,L2)
(k=3
), Lcomoment.coefficients(L4,L2)
(k=4
), and so on. Symbolically, the higher L-comoment coefficients for k \ge 3
are
\hat{\tau}_{k[12]} = \frac{\hat{\lambda}_{k[12]}}
{\hat{\lambda}_{2[12]}}\mbox{.}
Finally, the usual univariate L-moment ratios as seen from lmom.ub
or lmoms
are along the diagonal. The Lcomoment.coefficients
function does not make use of lmom.ub
or lmoms
.
An R list
is returned.
type |
The type of L-comoment representation in the matrix: “Lcomoment.coefficients”. |
order |
The order of the coefficients. |
matrix |
A |
The function begins with a capital letter. This is intentionally done so that lower case namespace is preserved. By using a capital letter now, then lcomoment.coefficients
remains an available name in future releases.
W.H. Asquith
Asquith, W.H., 2011, Distributional analysis with L-moment statistics using the R environment for statistical computing: Createspace Independent Publishing Platform, ISBN 978–146350841–8.
Serfling, R., and Xiao, P., 2007, A contribution to multivariate L-moments—L-comoment matrices: Journal of Multivariate Analysis, v. 98, pp. 1765–1781.
Lcomoment.matrix
, Lcomoment.coefficients
D <- data.frame(X1=rnorm(30), X2=rnorm(30), X3=rnorm(30))
L1 <- Lcomoment.matrix(D,k=1)
L2 <- Lcomoment.matrix(D,k=2)
L3 <- Lcomoment.matrix(D,k=3)
LkLCV <- Lcomoment.coefficients(L1,L2)
LkTAU3 <- Lcomoment.coefficients(L3,L2)
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