Poisson Process for 500 variates
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I would like to generate a code to produce a poisson process for N = 500 variates witk k is randomly between 1 and 10 and lambda = 12.
N = 500;
T = 1;
lambda = 12;
t = linspace(0, T, 100);
dt = t(2) - t(1);
S=cumsum([zeros(1,N); poissrnd(lambda*dt, length(t)-1, N) ]);
plot(t,S)
I generated this code by myself, bu I cannot use the random value of k between 1 and 10 , and 500-variates graph has too many lines, but I guess this result is totally wrong, how can I get rid of my mistakes and write the code properly?
Thanks a lot.
My second code is this
T = 1;
lambda = 12;
k=9;
t = linspace(0, T, 500);
for i = 1:500
f(i) = (lambda.^k) .* exp(-lambda) ./ factorial(k);
end
N = cumsum(f);
disp(N)
stairs(t,N(1:100))
But, again, the graph and estimations are totally wrong.
Accepted Answer
More Answers (3)
Sulaymon Eshkabilov
on 14 May 2020
Here is the alternative solution:
T = 1;
lambda = 12;
t = linspace(0, T, 500);
k=randi([1,10], 500);
f = (lambda.^k) .* exp(-lambda) ./ factorial(k);
N = sum(f);
disp(N);
stairs(t,N)
Good luck
Sulaymon Eshkabilov
on 14 May 2020
0 votes
Why not to use MATLAB's built in fcn: poissrnd()
3 Comments
Le Duc Long
on 25 Jun 2020
Hi Sulaymon Eshkabilov and Zeyneh Toprak,
I am also interested in this issue. My problem is to get the number of vehicles to an intersection with the Poisson distribution, lambda = 0.5 (vehicle/second). Can you help me code for vehicle traffic (numbers of vehicles) distributed by time period 500 seconds, step of time = 1 second?
Thanks so much!
Sa'adatu Abubakar
on 29 Jul 2021
Hello I'm also interested in the area please can you help me with the MATLAB code for poison arrival and general servive with single server?. Thank you
Sa'adatu Abubakar
on 29 Jul 2021
please I mean poisson arrival with general service and single server.
Najme Benvari
on 23 May 2023
0 votes
Hi I read the Poisson production code when the jump size is random and the intensity of the jumps is Stochastic and a CIR process. I will be very thankful.
1 Comment
Najme Benvari
on 25 May 2023
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