MATLAB: Poisson random number generator

ahmed

Hi all please i need to know how to generate a Poisson distributed random variable without using the built-in function (poissrnd).

Best Answer

If this is an acadamic exercise - you can look at the literature refererence

%   References:
%      [1]  Devroye, L. (1986) Non-Uniform Random Variate Generation,
%           Springer-Verlag.

Related Solutions

MATLAB: Compound Poisson Distribution Model

I am not sure if I understand your question correctly. I guess once you get P, then you would like to choose its elements randomly, right? If so, you can use the following code:

alpha = 1; beta = 1; % replace by your desired values
for k = 0:7
    fun = @(lambda) (lambda.^k).*(exp(-1.*lambda)).* gampdf(lambda,alpha,beta)./factorial(k);
    P(k+1) = integral(fun,0,Inf);
end
out = datasample(P,1) % 1 observation, replace 1 by higher value for more observations

This will be uniformly random. If you are interested then you may use:

out = P(randperm(numel(P),1))

MATLAB: Is there a better way to randomly generate a Doubly Stochastic Matrix

This looks promising. I have kept some notes in the comments so you can see what I was doing...

There are three lines of code that are commented out. If you uncomment them, and comment the line after the second one, you can check that these give the same results. Of course the timing is not fair under those circumstances, but with the code commented the timings show a fantastic speed difference for large values....

M = zeros(n,n);
I = eye(n);
tic  % Original method.
for k = 1:n
    pidx = GRPdur(n);  % Random Permutation
%     F{k} = pidx;     % Used to check same results below....
    P = I(pidx,:);     % Random P matrix
    M = M + c(k)*P;
end
toc
M2 = zeros(n,n);
tic  % proposed alternative
for k = 1:n
%     [~,idx] = sort(F{k});    % Used to compare same results.
    [~,idx] = sort(GRPdur(n)); % Or just idx = GRPdur(n);  ??
    idx = idx + (0:n-1)*n;     
    M2(idx) = M2(idx) + c(k);
end
toc
% max(abs(M2(:)-M(:)))  % Used to compare same results.

Best Answer

Related Solutions

MATLAB: Compound Poisson Distribution Model

MATLAB: Is there a better way to randomly generate a Doubly Stochastic Matrix

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