lmomco (version 0.88)

lmom.diff: Difference Between L-moments of the Distribution and the L-moments of the Data

Description

This function computes the difference between the L-moments derived from a parameterized distribution and the L-moments as computed from the data. This function is useful to characterize the bias that develops between the theoretical L-moments of a distribution and the L-moments of the data. This function also is an important test on the algorithms that fit distributions to the L-moments. The difference is computed as the L-moment from the distribution minus the L-moment of the data. The lmorph function is used internally to get the L-moment objects into the appropriate format.

Usage

lmom.diff(lmomparm, lmomdata,verbose=TRUE)

Arguments

lmomparm

L-moments of a distribution such as from par2lmom

lmomdata

L-moments of the data such as from lmom.ub

verbose

Logical switch on verbosity of output. Default is TRUE.

Value

• [1] "THE FIVE DIFFERENCES BETWEEN L-MOMENTS OF DISTRIBUTION AND DATA"

  [1] "Mean L2 TAU3 TAU4 TAU5"

  [1] -5.529431e-18 0.000000e+00 0.000000e+00 3.243155e-02

  where the five values are the differences between the theoretical L-moments of the fitted distribution and the sample L-moments of the data (theoretical minus sample) in the titled column. These values are also returned as part of an R list. If a list element has numeric(0) then likely one of the L-moments is NULL or NA for the distribution such as the results reported for the example involving the Generalized Logistic distribution (glo).

See Also

par2lmom, lmom2par, lmorph

Examples

# The first three moment differences are zero because the GLO is only 
  # fit to these and not the higher moments.
  lmr <- lmom.ub(rnorm(40))
  para <- lmom2par(lmr, type = 'glo')
  lmom.diff(par2lmom(para),lmr)

  # The first two moment differences are zero because the Normal is only 
  # fit to these and not the higher moments.
  lmr <- lmom.ub(rnorm(40))
  lmr <- lmorph(lmr)
  para <- parnor(lmr)
  lmom.diff(lmomnor(para),lmr)