parrevgum {lmomco}R Documentation

Estimate the Parameters of the Reverse Gumbel Distribution

Description

This function estimates the parameters of the Reverse Gumbel distribution given the type-B L-moments of the data in an L-moment object such as that returned by pwmRC using pwm2lmom. This distribution is important in the analysis of censored data. It is the distribution of a logarithmically transformed two-parameter Weibull distribution. The relation between distribution parameters and L-moments is

α = λ^B_2/lbracelog(2) + mathrm{Ei}(-2log(1-zeta)) - mathrm{Ei}(-log(1-zeta))rbracembox{ and}

xi = λ^B_1 + αlbracemathrm{Ei}(-log(1-zeta))rbracembox{,}

where zeta is the right-tail censoring fraction of the sample o the nonexceedance probability of the right-tail censoring threshold, and mathrm{Ei}(x) is the exponential integral defined as

mathrm{Ei}(X) = int_X^{infty} x^{-1}e^{-x}mathrm{d}x mbox{,}

where mathrm{Ei}(-log(1-zeta)) rightarrow 0 as zeta rightarrow 1 and mathrm{Ei}(-log(1-zeta)) can not be evaluated as zeta rightarrow 0.

Usage

parrevgum(lmom,zeta=1,checklmom=TRUE)

Arguments

lmom A L-moment object created by pwm2lmom through pwmRC or other L-moment type object. The user intervention of the zeta differentiates this distribution and hence this function from similar parameter estimation functions in the lmomco package.
zeta The right censoring fraction. Number of samples observed (noncensored) divided by the total number of samples.
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.

Value

An R list is returned.

type The type of distribution: revgum.
para The parameters of the distribution.
zeta The right censoring fraction. Number of samples observed (noncensored) divided by the total number of samples.
source The source of the parameters: “parrevgum”.

Author(s)

W.H. Asquith

References

Hosking, J.R.M., 1990, L-moments—Analysis and estimation of distributions using linear combinations of order statistics: Journal of the Royal Statistical Society, Series B, vol. 52, p. 105–124.

Hosking, J.R.M., 1995, The use of L-moments in the analysis of censored data, in Recent Advances in Life-Testing and Reliability, edited by N. Balakrishnan, chapter 29, CRC Press, Boca Raton, Fla., pp. 546–560.

See Also

pwm2lmom, pwmRC, cdfrevgum, quarevgum

Examples

# See p. 553 of Hosking (1995)
# Data listed in Hosking (1995, table 29.3, p. 553)
D <- c(-2.982, -2.849, -2.546, -2.350, -1.983, -1.492, -1.443, 
       -1.394, -1.386, -1.269, -1.195, -1.174, -0.854, -0.620,
       -0.576, -0.548, -0.247, -0.195, -0.056, -0.013,  0.006,
        0.033,  0.037,  0.046,  0.084,  0.221,  0.245,  0.296)
D <- c(D,rep(.2960001,40-28)) # 28 values, but Hosking mentions 40 values in total
z <-  pwmRC(D,threshold=.2960001)
str(z)
# Hosking reports B-type L-moments for this sample are 
# lamB1 = -.516 and lamB2 = 0.523
btypelmoms <- pwm2lmom(z$Bbetas)
# My version of R reports lamB1 = -0.5162 and lamB2 = 0.5218
str(btypelmoms)
rg.pars <- parrevgum(btypelmoms,z$zeta)
str(rg.pars)
# Hosking reports xi = 0.1636 and alpha = 0.9252 for the sample
# My version of R reports xi = 0.1635 and alpha = 0.9254

[Package lmomco version 0.96.3 Index]