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lmomco (version 2.4.14)

pp.f: Quantile Function of the Ranks of Plotting Positions

Description

There are two major forms (outside of the general plotting-position formula pp) for estimation of the \(p_r\)th probability of the \(r\)th order statistic for a sample of size \(n\): the mean is \(pp'_r = r/(n+1)\) (Weibull plotting position) and the Beta quantile function is \(pp_r(F) = IIB(F, r, n+1-r)\), where \(F\) represents the nonexceedance probability of the plotting position. \(IIB\) is the “inverse of the incomplete beta function” or the quantile function of the Beta distribution as provided in R by qbeta(f, a, b). If \(F=0.5\), then the median is returned but that is conveniently implemented in pp.median. Readers might consult Gilchrist (2011, chapter 12) and Karian and Dudewicz (2011, p. 510).

Usage

pp.f(f, x)

Value

An R

vector is returned.

Arguments

f

A nonexceedance probability.

x

A vector of data. The ranks and the length of the vector are computed within the function.

Author

W.H. Asquith

References

Gilchrist, W.G., 2000, Statistical modelling with quantile functions: Chapman and Hall/CRC, Boca Raton.

Karian, Z.A., and Dudewicz, E.J., 2011, Handbook of fitting statistical distributions with R: Boca Raton, FL, CRC Press.

See Also

pp, pp.median

Examples

Run this code
X <- sort(rexp(10))
PPlo <- pp.f(0.25, X)
PPhi <- pp.f(0.75, X)
plot(c(PPlo,NA,PPhi), c(X,NA,X))
points(pp(X), X) # Weibull i/(n+1)

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