This function estimates the L-moments of the Kappa distribution given the parameters (\(\xi\), \(\alpha\), \(\kappa\), and \(h\)) from parkap
. The L-moments in terms of the parameters are complicated and are solved numerically. If the parameter \(k = 0\) (is small or near zero) then let
$$d_r = \gamma + \log(-h) + \mathrm{digamma}(-r/h)\ \mbox{for}\ h < 0$$
$$d_r = \gamma + \log(r)\ \mbox{for}\ h = 0\ \mbox{(is small)}$$
$$d_r = \gamma + \log(h) + \mathrm{digamma}(1+r/h)\ \mbox{for}\ h > 0$$
or if \(k > -1\) (nonzero) then let
$$g_r = \frac{\Gamma(1+k)\Gamma(-r/h-k)}{-h^k\,\Gamma(-r/h)}\ \mbox{for}\ h < 0$$
$$g_r = \frac{\Gamma(1+k)}{r^k} \times (1-0.5hk(1+k)/r)\ \mbox{for}\ h = 0\ \mbox{(is small)}$$
$$g_r = \frac{\Gamma(1+k)\Gamma(1+r/h)}{h^g\,\Gamma(1+k+r/h)}\ \mbox{for}\ h > 0$$
where \(r\) is L-moment order, \(\gamma\) is Euler's constant, and for \(h = 0\) the term to the right of the multiplication is not in Hosking (1994) or Hosking and Wallis (1997) for exists within Hosking's FORTRAN code base.
The probability-weighted moments (\(\beta_r\); pwm2lmom
) for \(k = 0\) (is small or near zero) are
$$r\beta_{r-1} = \xi + (\alpha/\kappa)[1 - d_r]$$
or if \(k > -1\) (nonzero) then
$$r\beta_{r-1} = \xi + (\alpha/\kappa)[1 - g_r]$$
lmomkap(para, nmom=5)
An R
list
is returned.
Vector of the L-moments. First element is \(\lambda_1\), second element is \(\lambda_2\), and so on.
Vector of the L-moment ratios. Second element is \(\tau\), third element is \(\tau_3\) and so on.
Level of symmetrical trimming used in the computation, which is 0
.
Level of left-tail trimming used in the computation, which is NULL
.
Level of right-tail trimming used in the computation, which is NULL
.
An attribute identifying the computational source of the L-moments: “lmomkap”.
The parameters of the distribution.
The number of moments to compute. Default is 5.
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.
parkap
, cdfkap
, pdfkap
, quakap
lmr <- lmoms(c(123, 34, 4,78, 45, 234, 65, 2, 3, 5, 76, 7, 80))
lmomkap(parkap(lmr))
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