This function estimates the parameters of the Kappa distribution given the L-moments of the data in an L-moment object such as that returned by lmoms
. The relations between distribution parameters and L-moments are seen under lmomkap
, but of relevance to this documentation, the upper bounds of L-kurtosis (\(\tau_4\)) and a function of L-skew (\(\tau_3\)) is given by
$$\tau_4 < \frac{5\tau_3^2+1}{6}$$
This bounds is equal to the Generalized Logistic distribution (parglo
) and failure occurs if this upper bounds is exceeded. However, the argument snap.tau4
, if set, will set \(\tau_4\) equal to the upper bounds of \(\tau_4\) of the distribution to the relation above. This value of \(\tau_4\) should be close enough numerically The argument nudge.tau4
is provided to offset \(\tau_4\) downward just a little. This keeps the relation operator as “\(<\)” in the bounds above to match Hosking's tradition as his sources declare “\(\ge\)” as above the GLO. The nudge here hence is not zero, which is a little different compared to the conceptually similar snapping in paraep4
.
parkap(lmom, checklmom=TRUE,
snap.tau4=FALSE, nudge.tau4=sqrt(.Machine$double.eps), ...)
An R
list
is returned.
The type of distribution: kap
.
The parameters of the distribution.
The source of the parameters: “parkap”.
The support (or range) of the fitted distribution.
A numeric failure code.
A text message for the failure code.
An L-moment object created by lmoms
or vec2lmom
.
Should the lmom
be checked for validity using the are.lmom.valid
function. Normally this should be left as the default and it is very unlikely that the L-moments will not be viable (particularly in the \(\tau_4\) and \(\tau_3\) inequality). However, for some circumstances or large simulation exercises then one might want to bypass this check.
A logical to “snap” the \(\tau_4\) downwards to the lower boundary if the given \(\tau_4\) is greater than the boundary described as above.
An offset to the snapping of \(\tau_4\) intended to move \(\tau_4\) just below the upper bounds. (The absolute value of the nudge is made internally to ensure only downward adjustment by a subtraction operation.)
Other arguments to pass.
W.H. Asquith
Hosking, J.R.M., 1994, The four-parameter kappa distribution: IBM Journal of Reserach and Development, v. 38, no. 3, pp. 251--258.
Hosking, J.R.M., and Wallis, J.R., 1997, Regional frequency analysis---An approach based on L-moments: Cambridge University Press.
lmomkap
,
cdfkap
, pdfkap
, quakap