lmomgpaRC {lmomco}

B-type L-moments of the Generalized Pareto Distribution with Right-Tail Censoring

Description

This function computes the “B”-type L-moments of the Generalized Pareto distribution given the parameters (\xi, \alpha, and \kappa) from pargpaRC and the right-tail censoring fraction \zeta. The B-type L-moments in terms of the parameters are

\lambda^B_1 = \xi + \alpha m_1 \mbox{,}

\lambda^B_2 = \alpha (m_1 - m_2) \mbox{,}

\lambda^B_3 = \alpha (m_1 - 3m_2 + 2m_3)\mbox{,}

\lambda^B_4 = \alpha (m_1 - 6m_2 + 10m_3 - 5m_4)\mbox{, and}

\lambda^B_5 = \alpha (m_1 - 10m_2 + 30m_3 - 35m_4 + 14m_5)\mbox{,}

where m_r = \lbrace 1-(1-\zeta)^{r+\kappa}\rbrace/(r+\kappa) and \zeta is the right-tail censor fraction or the probability \mathrm{Pr}\lbrace \rbrace that x is less than the quantile at \zeta nonexceedance probability: (\mathrm{Pr}\lbrace x < X(\zeta) \rbrace). In other words, if \zeta = 1, then there is no right-tail censoring. Finally, the RC in the function name is to denote Right-tail Censoring.

Usage

lmomgpaRC(para)

Arguments

para

The parameters of the distribution. Note that if the \zeta part of the parameters (see pargpaRC) is not present then zeta=1 (no right-tail censoring) is assumed.

Value

An R list is returned.

lambdas

Vector of the L-moments. First element is \lambda_1, second element is \lambda_2, and so on.

ratios

Vector of the L-moment ratios. Second element is \tau, third element is \tau_3 and so on.

trim

Level of symmetrical trimming used in the computation, which is 0.

leftrim

Level of left-tail trimming used in the computation, which is NULL.

rightrim

Level of right-tail trimming used in the computation, which is NULL.

source

An attribute identifying the computational source of the L-moments: “lmomgpaRC”.

message

For clarity, this function adds the unusual message to an L-moment object that the lambdas and ratios are B-type L-moments.

zeta

The censoring fraction. Assumed equal to unity if not present in the gpa parameter object.

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, v. 52, pp. 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

pargpa, pargpaRC, lmomgpa, cdfgpa, pdfgpa, quagpa

Examples

para <- vec2par(c(1500,160,.3),type="gpa") # build a GPA parameter set
lmorph(lmomgpa(para))
lmomgpaRC(para) # zeta = 1 is internally assumed if not available
# The previous two commands should output the same parameter values from
# independent code bases.
# Now assume that we have the sample parameters, but the zeta is nonunity.
para$zeta = .8
lmomgpaRC(para) # The B-type L-moments.