lmom.diff {lmomco} | R Documentation |
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.
lmom.diff(lmomparm, lmomdata, verbose=TRUE, digits=4)
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 . |
digits |
Number of digits to pass internally to the signif function for rounding of results. |
"THE FIVE DIFFERENCES BETWEEN L-MOMENTS OF DISTRIBUTION AND DATA"
L1diff L2diff T3diff T4diff T5diff
1 0 -1.11e-16 -0.7345 -0.4005 -0.3942
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
).
W.H. Asquith
# 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)