Using Poisson Approximation to Compare Infection Rates in Village A and B

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Discussion Overview

The discussion revolves around the application of Poisson approximation to compare infection rates in two villages, A and B. Participants explore different methods to calculate the probability that the number of infections in village B exceeds that in village A, addressing both theoretical and practical aspects of using Poisson distributions and their approximations.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents two methods for calculating the probability that infections in village B exceed those in village A, using Poisson distributions and normal approximations.
  • Another participant questions the reasoning behind treating A-B as a Poisson distribution, seeking clarification on the validity of this approach.
  • There is a discussion about the properties of Poisson distributions, specifically that while A+B can be modeled as Poisson, A-B may not be validly treated in the same way.
  • Concerns are raised regarding the interpretation of the probabilities calculated, particularly that A-B cannot be negative if treated as a Poisson variable, which leads to a discussion about the implications of independence in Poisson processes.
  • A suggestion is made to run simulations to empirically test the results of the different methods proposed.

Areas of Agreement / Disagreement

Participants express differing views on the appropriateness of using Poisson distributions for linear combinations, particularly for A-B. There is no consensus on the validity of the second method or the interpretation of the results.

Contextual Notes

Participants note that the assumptions regarding independence and the nature of the distributions may affect the outcomes. The discussion highlights the complexity of applying Poisson approximations in this context.

qazxsw11111
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There are 60 infections in village A per month and 48 infections in village B per month.
Let A be no of infections in village A per month and B be no of infections in village B per month. Assume occurrence is independent and random.

So
Method 1 (Working method):

A~Po (60) and B~Po (48)

Using a suitable approximation, find the probability that in 1 month, the no of infections in B exceeds no of infections in A.

Since λ>10, A~ N(60,60) and B~N(48,48) approximately

B-A~(-12, 108)

P(B>A)=P(B-A>0)=0.115

This I can understand but when I tried another method, it didnt work.

Method 2: Through linear combination of poisson (?Cannot get it to work?)


A-B ~ Po(12)

Since λ>10, A-B~N(12,12)

P(A<B)=P(A-B<0)=2.66x10-4

Why the difference? Why does the second method not work?
 
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qazxsw11111 said:
A-B ~ Po(12)

Could you explain the reasoning for this step please?
 
I thought Poisson can perform linear combinations. I know A+B~Po(60+48) but A-B? I assumed minus is possible.
 
qazxsw11111 said:
I know A+B~Po(60+48) but A-B?

Ok. If A-B were Poisson, what would be the frequency, mean and variance values?
 
λ1+λ2 in poisson formula is e^-(λ1+λ2)=e^-λ1*e^-λ2. but if you use λ1-λ2 we have e^-(λ1-λ2)=e^-λ1*e^λ2=e^λ2/e^λ1
 
qazxsw11111 said:
I thought Poisson can perform linear combinations.

Linear combinations of Poisson random variables are actually Compound Poisson - not pure Poisson but an interesting topic in their own right.

qazxsw11111 said:
P(A-B<0)=2.66x10-4

On second thought, if A-B were Poisson then A-B can _never_ be negative, i.e. the probability would be exactly zero - but since A and B are independent Poisson there's always some chance. If you have access to math or stats software then it would be useful to run some random simulations to check which answer is correct.

Have fun!
 

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