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lmomco (version 0.88)

pwm.ub: Unbiased Sample Probability-Weighted Moments

Description

Unbiased sample Probability-Weighted Moments (PWMs) are computed from a sample. The first five $\beta_r$'s are computed by default.

$$\beta_r = n^{-1}\sum^n_{j=1} (j-1 \choose r)x_{j:n}$$

Usage

pwm.ub(x,nmom=5,sort=TRUE)

Arguments

x
A vector of data values.
nmom
Number of PWMs to return.
sort
Does the data need sorting? The computations require sorted data. This option is provided to optimize processing speed if presorted data already exists.

Value

  • An R list is returned.
  • betasThe PWMs. Note that convention is the have a $\beta_0$, but this is placed in the first index i=1 of the betas vector.
  • sourceSource of the PWMs: pwm.ub

References

Greenwood, J.A., Landwehr, J.M., Matalas, N.C., and Wallis, J.R., 1979, Probability weighted moments---Definition and relation to parameters of several distributions expressable in inverse form: Water Resources Research, vol. 15, p. 1,049--1,054.

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. and Wallis, J.R., 1997, Regional frequency analysis---An approach based on L-moments: Cambridge University Press.

See Also

pwm.pp, pwm.gev, pwm2lmom

Examples

Run this code
pwm <- pwm.ub(rnorm(20))

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