$$p_i = \frac{i-0.35}{n} \mbox{,}$$
where $pp_i$ is the nonexceedance probability $F$ of the $i$th ascending data values. The parameters $A$ and $B$ together specify the plotting-position type, and $n$ is the sample size. The PWMs are computed by
$$\beta_r = n^{-1}\sum_{i=1}^{n}p_i^r \times x_{j:n} \mbox{,}$$
where $x_{j:n}$ is the $j$th order statistic
$x_{1:n} \le x_{2:n} \le x_{j:n} \dots \le x_{n:n}$ of random variable X, and
$r$ is $0, 1, 2, \dots$. Finally, pwm.gev dispatches to pwm.pp(data,A=-0.35,B=0) and does not
have its own logic.
pwm.gev(x)list is returned.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.
pwm.ub, pwm.pp, pwm2lmom