adding two different distributions example:Gaussian and Poisson distribution
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if we add two different distributions namely gaussian which as mean and standard deviation as variables and Poisson distribution with lambda variable how to mathematically relate the resultant distribution(What distribution the resulting value will take) and how to code it
1 件のコメント
Image Analyst
2016 年 6 月 8 日
What does "relate" mean to you? The new distribution will be the sum of the two you summed. What else do you need to know?
回答 (1 件)
If X ~ Poisson(lambda), Y ~ N(mu,sigma^2), X, Y independent and Z=X+Y, then the cdf of Z is given by
P(Z<=z) = sum_{k=0}^{k=oo} P(X=k) * P(Y<=z-k).
P(X=k) = lambda^k/k! * exp(-lambda)
P(Y<=z-k) = 0.5*(1+erf((z-k-mu)/sqrt(2*sigma^2))) (erf: error function)
If needed, you can get the pdf of Z by differentiating the sum with respect to z.
Best wishes
Torsten.
3 件のコメント
Anusha S S
2016 年 6 月 8 日
Torsten
2016 年 6 月 8 日
So to get the cfd F_Z of Z=X+Y, you have to evaluate the infinite sum
F_Z(z)= sum_{k=0}^{k=Inf} lambda^k/k!*exp(-lambda)*0.5*(1+erf((z-k-mu)/sqrt(2*sigma^2)))
for different values of z.
Make an attempt. If it does not work, post the code with the error message you get.
Best wishes
Torsten.
Torsten
2016 年 6 月 8 日
In Mathematica, the result for lambda=0.5, mu=0 and sigma=1 can be seen here:
Best wishes
Torsten.
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