Poisson Distribution (for a newbie)

[diffuser78]

I am simulating an event where users come into the pool randomly
starting at time T=0, i.e. For Example, 2 users came at T= 0 into the
the pool, 3 users came at T= 1 into the the pool, 5 users came at T=2
,..........,54 users came at T=45 etc. As cumulative number of users
goes above 1024, we stop the process.

I want to mimic such kind of distribution using poison traffic ( a bell
shaped curve). I looked into wikipedia and some other tutorials but I
wasn't sure how many parameter does the above kind of distribution
would require.

Could somebody put some light on this issue.

PS:: This is not exactly a programming issue but since I was using it
in one of the Python programs, I thought somebody might have used
similar thing in past and could help. Thanks.

 

[Duncan Smith]

I am simulating an event where users come into the pool randomly
starting at time T=0, i.e. For Example, 2 users came at T= 0 into the
the pool, 3 users came at T= 1 into the the pool, 5 users came at T=2
,..........,54 users came at T=45 etc. As cumulative number of users
goes above 1024, we stop the process.

I want to mimic such kind of distribution using poison traffic ( a bell
shaped curve). I looked into wikipedia and some other tutorials but I
wasn't sure how many parameter does the above kind of distribution
would require.

Could somebody put some light on this issue.

PS:: This is not exactly a programming issue but since I was using it
in one of the Python programs, I thought somebody might have used
similar thing in past and could help. Thanks.

The Poisson has one parameter, its mean. See e.g.
http://www.itl.nist.gov/div898/handbook/eda/section3/eda366j.htm

Duncan

 

[Jeremy Sanders]

I want to mimic such kind of distribution using poison traffic ( a bell
shaped curve). I looked into wikipedia and some other tutorials but I
wasn't sure how many parameter does the above kind of distribution
would require.

I've used numarray's poisson distribution generator, which was very useful.
There may well be something similar in NumPy/Numeric/SciPy.

e.g.

from numarray.random_array import poisson

for i in xrange(100):
print poisson(10)

Where 10 is the mean.

Jeremy