A question about Poisson process (waiting online)

In summary: My guess - a mistake in the derivation. E[N_t^2]=\lambda t looks wrong (unless the mean=0). It is the variance.
  • #1
ssyldy
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Hey guys, I encounter a question (maybe a silly one )that puzzles me. Nt is a Poisson process and λ is the jump intensity.Since the quadratic variation of Poisson process is [N,N]t=Nt, and Nt2-[N,N]t is a martingale, it follows that E[Nt2]=E[[N,N]t]=λ*t. On the other hand, the direct calculation of E[Nt2] can be found in https://proofwiki.org/wiki/Variance_of_Poisson_Distribution, which indicates E[Nt2]=(t*λ)2+t*λ. The two results are different. I really appreciate it if somebody can help me.
 
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  • #2
It would help to know the context of that calculation and the meaning of the individual symbols.
 
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  • #3
Nt is a Poisson process and λ is the jump intensity.Since the quadratic variation of Poisson process is [N,N]t=Nt, and Nt2-[N,N]t is a martingale, it follows that E[Nt2]=E[[N,N]t]=λ*t. On the other hand, the direct calculation of E[Nt2] can be found in https://proofwiki.org/wiki/Variance_of_Poisson_Distribution
 
  • #4
ssyldy said:
Hey guys, I encounter a question (maybe a silly one )that puzzles me. Nt is a Poisson process and λ is the jump intensity.Since the quadratic variation of Poisson process is [N,N]t=Nt, and Nt2-[N,N]t is a martingale, it follows that E[Nt2]=E[[N,N]t]=λ*t. On the other hand, the direct calculation of E[Nt2] can be found in https://proofwiki.org/wiki/Variance_of_Poisson_Distribution, which indicates E[Nt2]=(t*λ)2+t*λ. The two results are different. I really appreciate it if somebody can help me.
It looks like someone has confused the second moment with the variance.
 
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  • #5
mathman said:
It looks like someone has confused the second moment with the variance.
Hi dude, seems like you know the answer. Could you explain?
 
  • #6
ssyldy said:
Hi dude, seems like you know the answer. Could you explain?
General formulas for a random variable X:
second moment: [itex]E(X^2)[/itex]
variance: [itex]E(X^2)-(E(X))^2[/itex]
 
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  • #7
mathman said:
General formulas for a random variable X:
second moment: [itex]E(X^2)[/itex]
variance: [itex]E(X^2)-(E(X))^2[/itex]
Yeah, I know that. But my question is, why would I get two different results of E[Nt2] using two different methods?
 
  • #8
ssyldy said:
Yeah, I know that. But my question is, why would I get two different results of E[Nt2] using two different methods?
My guess - a mistake in the derivation. [itex]E[N_t^2]=\lambda t[/itex] looks wrong (unless the mean=0). It is the variance.
 
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Related to A question about Poisson process (waiting online)

1. What is a Poisson process?

A Poisson process is a statistical model that describes the occurrence of events over a continuous period of time. It is characterized by the assumption that events occur independently and randomly, with a constant average rate.

2. How is a Poisson process different from a normal distribution?

A Poisson process is different from a normal distribution in that it specifically models the occurrence of discrete events over time, whereas a normal distribution models continuous variables. Additionally, a normal distribution assumes a fixed mean and standard deviation, while a Poisson process assumes a fixed average rate of event occurrence.

3. What is the formula for calculating the probability of a certain number of events occurring in a Poisson process?

The formula for calculating the probability of a certain number of events (k) occurring in a Poisson process is: P(k events) = (λ^k * e^(-λ)) / k!, where λ is the average rate of event occurrence.

4. How is a Poisson process used in real-world applications?

Poisson processes are commonly used in a variety of fields, including finance, engineering, and telecommunications, to model the occurrence of events such as customer arrivals, machine breakdowns, and network traffic. They can also be used to analyze data on natural phenomena, such as earthquakes or hurricanes.

5. Can a Poisson process have a non-integer value for λ (average rate of event occurrence)?

Yes, a Poisson process can have a non-integer value for λ. This is because λ represents the average rate of event occurrence over a continuous period of time, and events can occur at any fractional rate within that time frame.

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