Description Usage Arguments Details Value Note Author(s) References See Also Examples

Compute the L-comoments from a rectangular `data.frame`

containing arrays of random variables. The order of the L-comoments is specified.

1 | ```
Lcomoment.matrix(DATAFRAME, k=1)
``` |

`DATAFRAME` |
A convential |

`k` |
The order of the L-comoments to compute. Default is |

L-comoments are computed for each item in the `data.frame`

. L-comoments of order *k = 1* are means and co-means. L-comoments of order *k = 2* are L-scale and L-coscale values. L-comoments of order *k = 3* are L-skew and L-coskews. L-comoments of order *k = 4* are L-kurtosis and L-cokurtosis, and so on. The usual univariate L-moments of order *k* as seen from `lmom.ub`

or `lmoms`

are along the diagonal. This function does not make use of `lmom.ub`

or `lmoms`

. The function `Lcomoment.matrix`

calls `Lcomoment.Lk12`

for each cell in the matrix. The L-comoment matrix for *d*-random variables is

* \mbox{\boldmath $Λ_k$} = (\hat{λ}_{k[ij]})
*

computed over the pairs (*X^{(i)},X^{(j)}*) where *1 ≤ i ≤ j ≤ d*.

An **R** `list`

is returned.

`type` |
The type of L-comoment representation in the matrix: “Lcomoments”. |

`order` |
The order of the matrix—specified by k in the argument list. |

`matrix` |
A kth order L-comoment matrix. |

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.matrix`

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.Lk12`

, `Lcomoment.coefficients`

1 2 3 | ```
D <- data.frame(X1=rnorm(30), X2=rnorm(30), X3=rnorm(30))
L1 <- Lcomoment.matrix(D,k=1)
L2 <- Lcomoment.matrix(D,k=2)
``` |

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