getells0.m (1219B)
1 %%% Returns values of s_o and l_o such that d(l)_0 - g_s* and d(s)_0 - g_s* and d(sigma)_0 are minimized, given all other model parameters (note that you don't need a transition path for this). 2 %%% Gotcha: d(some variable) is that variable's derivative. In the paper, this is that variable with a hat ^. 3 4 function xsoln=getells0(xguess,dlta0,Nend, alpha,epsilon,beta,lambda,phi,dltabar,ubar,gamma,rho,z,y,sigma,nbar,gs, T); 5 6 %%% Use minimization to ensure ellhat=gs, shat=gs, and sigmahat=0 7 %%% as closely as possible, by choosing x=[s0 ell0 N0]. 8 9 options=optimset('Display','on', 'MaxFunEvals', 100000, 'MaxIter', 1000); 10 %%% options=optimset('Display','on'); 11 xsoln=fminsearch(@SSR,xguess,options); 12 %%% xsoln=fminunc(@SSR,xguess,options); 13 %%% fminsearch attempts to find the minimum of a function. 14 15 function e=SSR(x0); 16 s=x0(1); 17 ell=x0(2); 18 19 x=[s ell sigma dlta0 y z Nend]; 20 t=T; 21 22 dx=transit1dx(t,x,alpha,epsilon,beta,lambda,phi,dltabar,ubar,gamma,rho,nbar, 0); 23 dx=dx'; %%% [s ell sigma dlta y z] 24 shat=dx(:,1)./s; 25 ellhat=dx(:,2)./ell; 26 sigmahat=dx(:,3)./sigma; 27 28 29 m(1)=shat-gs; 30 m(2)=ellhat-gs; 31 m(3)=sigmahat; 32 33 m=m'; 34 e=100*m'*m; %%% Sum of squared deviations 35 end 36 end