nsRFA (version 0.6-4)

varLmoments: Exact variance structure of sample L-moments

Description

varLmoments provides distribution-free unbiased estimators of the variances and covariances of sample L-moments.

Usage

varLmoments (x, matrix=TRUE)
 varLCV (x)
 varLCA (x)
 varLkur (x)

Arguments

x

vector representing a data-sample

matrix

if TRUE (default), the matrix of estimates of the variance structure (variance and covariance) i of sample L-moments is returned; if FALSE, a vector containing $var(l_1)$, $var(l_2)$, $var(l_3)$, $v

Value

• varLmoments gives the matrix of unbiased estimates of the variance structure of sample L-moments: this is a 4x4 matrix containg $var(l_1)$, $var(l_2)$, $var(l_3)$, $var(l_4)$ on the main diagonal, and the correspondant covariances elsewhere ($cov(l_1,l_2)$, $cov(l_1,l_3)$, etc.);

  varLCV gives the unbiased estimate of the variance of sample coefficient of L-variation of x;

  varLCA gives the unbiased estimate of the variance of sample L-skewness of x;

  varLkur gives the unbiased estimate of the variance of sample L-kurtosis of x.

Details

The estimation of the exact variance structure of sample L-moments is based on Elamir et Seheult (2004).

See Also

var, Lmoments.

Examples

x <- rnorm(30,10,2)
varLmoments(x)
varLmoments(x, FALSE)

varLCV(x)
varLCA(x)
varLkur(x)

data(hydroSIMN)
x <- annualflows["dato"][,]
cod <- annualflows["cod"][,]
dvarLmom <- function(x) {diag(varLmoments(x))}
sapply(split(x,cod),dvarLmom)