cdf2lmoms: Compute L-moments from Cumulative Distribution Function

Description

Compute the L-moments from a cumulative distribution function. For \(r \ge 1\), the L-moments can be computed by sequential calling of cdf2lmom. Consult the documentation of that function for mathematical definitions.

Usage

cdf2lmoms(para, nmom=6, fdepth=0, silent=TRUE, lambegr=1, ...)

Value

An R

list is returned.

lambdas: Vector of the L-moments. First element is \(\hat{\lambda}^{(0,0)}_1\), second element is \(\hat{\lambda}^{(0,0)}_2\), and so on.
ratios: Vector of the L-moment ratios. Second element is \(\hat{\tau}^{(0,0)}\), third element is \(\hat{\tau}^{(0,0)}_3\) and so on.
trim: Level of symmetrical trimming used in the computation, which will equal NULL is not support for trimming is provided by this function.
leftrim: Level of left-tail trimming used in the computation, which will equal NULL is not support for trimming is provided by this function.
rightrim: Level of right-tail trimming used in the computation, which will equal NULL is not support for trimming is provided by this function.
source: An attribute identifying the computational source of the L-moments: “cdf2lmoms”.

Arguments

para: The parameters from lmom2par or similar.
nmom: The number of moments to compute. Default is 6.
fdepth: The depth of the nonexceedance/exceedance probabilities to determine the lower and upper integration limits through a call to the par2qua function. The default of 0 implies the quantile for \(F=0\) and quantile for \(F=1\) as the respective lower and upper limits.
silent: A logical to be passed into cdf2lmom and then onto the try functions encompassing the integrate function calls.
lambegr: The \(r\)th order to begin the sequence for L-moment computation. Can be used as a means to bypass a mean computation if the user has an alternative method for the mean or other central tendency characterization in which case lambegr = 2.
...: Additional arguments to pass to cdf2lmom.

Author

W.H. Asquith

Examples

Run this code

cdf2lmoms(vec2par(c(10,40), type="ray"))
if (FALSE) {
# relatively slow computation
vec2par(c(.9,.4), type="emu"); cdf2lmoms(para, nmom=4)
vec2par(c(.9,.4), type="emu"); cdf2lmoms(para, nmom=4, fdepth=0)}