parray: Estimate the Parameters of the Rayleigh Distribution

In wasquith/lmomco: L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions

Estimate the Parameters of the Rayleigh Distribution

Description

This function estimates the parameters of the Rayleigh distribution given the L-moments of the data in an L-moment object such as that returned by lmoms. The relations between distribution parameters and L-moments are

\alpha = \frac{2\lambda_2\sqrt{\pi}}{\sqrt{2} - 1}\mbox{,}

and

\xi = \lambda_1 - \alpha\sqrt{\pi/2}\mbox{.}

Usage

parray(lmom, xi=NULL, checklmom=TRUE, ...)

Arguments

lmom	An L-moment object created by lmoms or vec2lmom.
xi	The lower limit of the distribution. If \xi is known then alternative algorithms are triggered and only the first L-moment is required for fitting.
checklmom	Should the lmom be checked for validity using the are.lmom.valid function. Normally this should be left as the default and it is very unlikely that the L-moments will not be viable (particularly in the \tau_4 and \tau_3 inequality). However, for some circumstances or large simulation exercises then one might want to bypass this check.
...	Other arguments to pass.

Value

An R list is returned.

type	The type of distribution: ray.
para	The parameters of the distribution.
source	The source of the parameters: “parray”.

Author(s)

W.H. Asquith

References

Hosking, J.R.M., 1986, The theory of probability weighted moments: Research Report RC12210, IBM Research Division, Yorkton Heights, N.Y.

See Also

lmomray, cdfray, pdfray, quaray

Examples

lmr <- lmoms(rnorm(20))
parray(lmr)

wasquith/lmomco documentation built on Nov. 13, 2024, 4:53 p.m.