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clear;
clc;
close all;
N = 50000; % number of agents to simulate
T = 61*4; % number quarters to live, from 25 to 85
kz = 7; % nodes for z
ke = 3;
rhoz = 0.9908;
sz = 0.0761;
se = 0.4869;
time = (1 : 1 : T)';
lambdat = 0.07982636 - 0.02322307 * (time/4 + 25) + 0.00105409 * (time/4 + 25).^2 - 0.00001028 * (time/4 + 25).^3;
x = [rhoz; sz; se ];
lb = [0.975; 0.03; 0.3];
ub = [0.997; 0.15; 0.8];
ftarget = @(x) incomemoments(x, N, T, lambdat, kz, ke);
ftarget(x)
%{
switch 'simplex'
case 'ga'
gaoptions = gaoptimset('Display', 'off','UseParallel', 'always', 'InitialPopulation', x');
x = ga(@(x)ftarget(x), size(x, 1), [], [], [], [], lb, ub, [], gaoptions);
case 'simplex'
x = neldmead_bounds(@(x)ftarget(x), x, lb, ub);
case 'particleswarm'
options = optimoptions('particleswarm', 'Display', 'off', 'MaxTime', 100, 'UseParallel', true, 'InitialSwarm', x', 'SwarmSize', 200);
x = particleswarm(ftarget, numel(x), lb', ub', options); %this function complains if I give it a structure as input
case 'patternsearch'
options = optimoptions('patternsearch','Display','off', 'UseParallel', true);
x = patternsearch(ftarget, x, [], [], [], [], lb, ub, [], options);
end
se = (1 - 0.55)^(1/2)*se; % Krueger Perri (2011) show 55% of the variance of trans compon is measurement error so subtract
%} |