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% rspdfsolv() - sub-function used by rsfit() to searc for optimal
% parameter for Ramberg-Schmeiser distribution
%
% Usage: res = rspdfsolv(l, l3, l4)
%
% Input:
% l - [lambda3 lamda4] parameters to optimize
% skew - expected skewness
% kurt - expected kurtosis
%
% Output:
% res - residual
%
% Author: Arnaud Delorme, SCCN, 2003
%
% See also: rsget()
%
% Reference: Ramberg, J.S., Tadikamalla, P.R., Dudewicz E.J., Mykkytka, E.F.
% A probability distribution and its uses in fitting data.
% Technimetrics, 1979, 21: 201-214.
% Copyright (C) 2003 Arnaud Delorme, SCCN, arno@salk.edu
%
% This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program; if not, write to the Free Software
% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
function res = rspdfsolv( l, a3, a4);
A = 1/(1 + l(1)) - 1/(1 + l(2));
B = 1/(1 + 2*l(1)) + 1/(1 + 2*l(2)) - 2*beta(1+l(1), 1+l(2));
C = 1/(1 + 3*l(1)) - 1/(1 + 3*l(2)) ...
- 3*beta(1+2*l(1), 1+l(2)) + 3*beta(1+l(1), 1+2*l(2));
D = 1/(1 + 4*l(1)) + 1/(1 + 4*l(2)) ...
- 4*beta(1+3*l(1), 1+l(2)) - 4*beta(1+l(1), 1+3*l(2)) ...
+ 6*beta(1+2*l(1), 1+2*l(2));
estim_a3 = (C - 3*A*B + 2*A^3)/(B-A^2)^(3/2);
estim_a4 = (D - 4*A*C + 6*A^2*B - 3*A^4)/(B-A^2)^2;
res = (estim_a3 - a3)^2 + (estim_a4 - a4)^2;
% the last term try to ensures that l(1) and l(2) are of the same sign
if sign(l(1)*l(2)) == -1, res = 2*res; end;
return;
% original equations
% $$$ A = 1(1 + l(3)) - 1/(1 + l(4));
% $$$ B = 1(1 + 2*l(3)) + 1/(1 + 2*l(4)) - 2*beta(1+l(3), 1+l(4));
% $$$ C = 1(1 + 3*l(3)) - 1/(1 + 3*l(4)) ...
% $$$ - 3*beta(1+2*l(3), 1+l(4)) + 3*beta(1+l(3), 1+2*l(4));
% $$$ D = 1(1 + 4*l(3)) + 1/(1 + 4*l(4)) ...
% $$$ - 4*beta(1+3*l(3), 1+l(4)) - 4*beta(1+l(3), 1+3*l(4)) ...
% $$$ + 6*beta(1+2*l(3), 1+2*l(4));
% $$$
% $$$ R(1) = l(1) + A/l(2);
% $$$ R(2) = (B-A^2)/l(2)^2;
% $$$ R(3) = (C - 3*A*B + 2*A^3)/l(2)^3;
% $$$ R(4) = (D - 4*A*C + 6*A^2*B - 3*A^4)/l(2)^4;