蒙特卡罗法模拟matlab源程序.zip

% Example Monte Carlo Simulation in Matlab % Function: y = x2^2/x1 % % Generate n samples from a normal distribution % r = ( randn(n,1) * sd ) + mu % mu : mean % sd : standard deviation % % Generate n samples from a uniform distribution % r = a + rand(n,1) * (b-a) % a : minimum % b : maximum n = 100000; % The number of function evaluations % --- Generate vectors of random inputs % x1 ~ Normal distribution N(mean=100,sd=5) % x2 ~ Uniform distribution U(a=5,b=15) x1 = ( randn(n,1) * 5 ) + 100; x2 = 5 + rand(n,1) * ( 15 - 5 ); % --- Run the simulation % Note the use of element-wise multiplication y = x2.^2 ./ x1; % --- Create a histogram of the results (50 bins) hist(y,50); % --- Calculate summary statistics y_mean = mean(y) y_std = std(y) y_median = median(y)