function [gdt,vdt,adt,fdt]=nolin_dynls(MT,y,g,v,ord,per)

% NOLIN_DYNLS        Identifies the hyperparameter values using dynamic
% lengthscale algorithm.
%
%   [gdt,vdt,adt,fdt] = NOLIN_DYNLS(MT,y,g,v,ord,per)
%
% Inputs:
%       MT  = Input time-series explanatory variables
%       y   = Corresponding output vector
%       g   = Starting initial of the lengthscale hyperparameter value
%       v   = Starting initial of the noise hyperparameter value
%       ord = Order of the reduction in the state-space dataset
%       per = Percentage value of confidence level
%
% Outputs:
%       gdt     = List of lengthscale hyperparameter values
%       vdt     = List of noise hyperparameter values
%       adt     = List of amplitude hyperparameter values
%       fdt     = List of final function value evaluation
%
%
% (C) Gaussian Process SSTS Toolbox 1.0
% (C) Copyright 2006-2007, Keith Neo <keith.neo@nuim.ie>
%                          http://www.hamilton.ie

k_disp=0;   % if "1", show display, else no display.
% dn=floor(sqrt(6/g)/(MT(2)-MT(1)));      % 6 used because of 5% minimum value.
% dn=2*floor(sqrt(6/g)/(MT(2)-MT(1)));    % This is last used, effective!
dn=floor(sqrt(-2*log(per)/g)/(MT(2)-MT(1)));

n=length(MT);
ss_n=getord_vec(ord,(1:n)');
K=length(ss_n);
gdt=zeros(K,1);
vdt=zeros(K,1);
adt=zeros(K,1);
fdt=zeros(K,1);
OPT=optimset('Display','off','GradObj','on','LargeScale','on','Hessian','on');
if (k_disp==1), figure(1),clf;hold on;
end
for k=1:K
    ind=ss_n(k);
    if (ind<=dn)
        tmpM=MT(1:ind+dn);
        tmpY=y(1:ind+dn);
    elseif ((n-ind)<=dn)
        tmpM=MT(ind-dn:n);
        tmpY=y(ind-dn:n);
    else
        tmpM=MT(ind-dn:ind+dn);
        tmpY=y(ind-dn:ind+dn);
    end
    xdt=[g;v];
    [logmaxdt,fval]=fminunc('nolin_hess_optag',log(xdt),OPT,tmpM,tmpY);
    gdt(k)=exp(logmaxdt(1));
    vdt(k)=exp(logmaxdt(2));
    adt(k)=nolin_a(tmpM,tmpY,exp(logmaxdt));
    fdt(k)=fval;
    if (k_disp==1)
        Q=diagadd(expacov(tmpM,tmpM,[1 gdt(k)]),vdt(k));
        prt=tmpY-vdt(k)*(Q\tmpY);
        figure(1),plot(tmpM,tmpY,'x');plot(tmpM,prt,'r');
        pause(0.01);
    end
end
if (k_disp==1), figure(1),hold off;
end