| clear;
|
| clc;
|
| close all;
|
|
|
| N = 50000;
|
| T = 61*4;
|
|
|
| kz = 7;
|
| 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
|
|
|
|
|
| %} |
