This function uses a Monte Carlo Markov Chain algorithm to infer parameters for an ODE model

test_gamma()

function test_gamma()
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Name - test_gamma
% Creation Date - 17th Feb 2012
% Author - Soumya Banerjee
% Website - www.cs.unm.edu/~soumya
%
%
% Description -
% Function to experiemnt with different parameters for the gamma
% distribution and find out the best values to get capsigma_powerminus2
% equal to roughly 0.3 with tight distribution around it
%
%
% License - BSD
%
% Change History -
% 17th Feb 2012 - Creation by Soumya Banerjee
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% a = 0; b = 0.01;
% a = 3; b = 0.01;
% for i = 1:1000
% x(i) = gamrnd(a + 36,b);
% end
a = 23; b = 0.01;
m1 = 5; m2 = 5; m3 = 5;
for i = 1:1000
x(i) = gamrnd(a + m1 + m2 + m3,b);
end
% figure
% plot(x)
figure
hist(x,20)