How to simulate T by inverse transform method
이전 댓글 표시
function T01 = simulate_T01(lambda, mu1, n_simulations)
u = rand(1, n_simulations);
T01 = -1 / (lambda + mu1) * log(1 - ((lambda + mu1) / lambda) * u);
end
It gives NaN.
The cdf is defined P(T<t)=\frac{\lambda}{\lambda+\mu_1} \left( 1-e^{-(\lambda+\mu_1)t}\right). How to simulate t?
It gives NaN since u is from [0,1]
채택된 답변
lambda = 5; % Replace with your value for lambda
mu1 = 3; % Replace with your value for mu1
n_simulations = 1000; % The number of random values you want to simulate
% Call the function
T01 = simulate_T01(lambda, mu1, n_simulations);
% Display the simulated times
disp(T01);
% Plot the data
figure; % Creates a new figure window
plot(T01, 'o-'); % Plot T01 with circle markers connected by lines
title('Simulated Times T01');
xlabel('Simulation Index');
ylabel('Time');
grid on; % Adds a grid to the plot for better readability
function T01 = simulate_T01(lambda, mu1, n_simulations)
% Ensure that lambda and mu1 are positive to avoid complex numbers
if lambda <= 0 || mu1 <= 0
error('Lambda and mu1 must be positive.');
end
% Scale u to the range of [0, lambda/(lambda + mu1)]
u = rand(1, n_simulations) * (lambda / (lambda + mu1));
% Apply the inverse CDF transform to get T01
T01 = -1 / (lambda + mu1) * log(1 - u);
end
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