Learn R Programming

lmomco (version 0.6)

pwm2lmom: Probability-Weighted Moments to L-moments

Description

Converts the Probability-Weighted Moments (PWM) to the L-moments given the PWM. The conversion is linear so procedures based on PWMs and identical to those based on L-moments.

$$\lambda_1 = \beta_0 \mbox{,}$$ $$\lambda_2 = 2\beta_1 - \beta_0 \mbox{,}$$ $$\lambda_3 = 6\beta_2 - 6\beta_1 + \beta_0 \mbox{,}$$ $$\lambda_4 = 20\beta_3 - 30\beta_2 + 12\beta_1 - \beta_0 \mbox{,}$$ $$\lambda_5 = 70\beta_4 - 140\beta_3 + 90\beta_2 - 20\beta_1 + \beta_0 \mbox{,}$$ $$\tau = \lambda_2/\lambda_1 \mbox{,}$$ $$\tau_3 = \lambda_3/\lambda_2 \mbox{,}$$ $$\tau_4 = \lambda_4/\lambda_2 \mbox{, and}$$ $$\tau_5 = \lambda_5/\lambda_2 \mbox{.}$$

Usage

pwm2lmom(pwm)

Arguments

pwm
A PWM object created by pwm.ub or similar.

Value

  • An R list is returned.
  • L1Arithmetic mean
  • L2L-scale---analogous to standard deviation
  • LCVcoefficient of L-variation---analogous to coe. of variation
  • TAU3The third L-moment ratio or L-skew---analogous to skew
  • TAU4The fourth L-moment ratio or L-kurtosis---analogous to kurtosis
  • TAU5The fifth L-moment ratio
  • L3The third L-moment
  • L4The fourth L-moment
  • L5The fifth L-moment

Details

The Probability Weighted Moments (PWMs) are linear combinations of the L-moments and therefore contain the same statistical information of the data as the L-moments. However, the PWMs are harder to interpret as measures of probability distributions. The linearity between L-moments and Probability-Weighted Moments means that procedures base on one are equivalent to the other.

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., 1996, FORTRAN routines for use with the method of L-moments: Version 3, IBM Research Report RC20525, T.J. Watson Research Center, Yorktown Heights, New York.

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

See Also

lmom.ub, pwm.ub, lmom2pwm

Examples

Run this code
lmom <- pwm2lmom(pwm.ub(c(123,34,4,654,37,78)))

pwm2lmom(pwm.ub(rnorm(100)))

Run the code above in your browser using DataLab