Conditional Expectation Value of Poisson Arrival in Fixed T

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Discussion Overview

The discussion revolves around the conditional expectation values of arrival times in a Poisson process within a fixed time interval. Participants explore the mathematical formulation of expected arrival times for the first, second, and third events, considering the properties of the Poisson process and the exponential distribution of inter-arrival times.

Discussion Character

  • Mathematical reasoning
  • Exploratory
  • Debate/contested

Main Points Raised

  • Post 1 presents a method to calculate the conditional expectation value of the first arrival time given it occurs within a fixed interval, leading to a derived expression for ##E[T_{1}|T_{1}\le T]##.
  • Post 2 introduces an alternative approach that considers the expected time of the nth event given exactly m events occurred in the interval, suggesting a formula for ##E[n,m,T]##.
  • Post 3 seeks clarification on the number of events within the interval and proposes a perspective that the expected arrival time of subsequent events should be greater than the first arrival and less than T.
  • Post 4 reiterates the uncertainty regarding the number of events in the interval and references the summation over all possible m in the context of the expected time calculations.

Areas of Agreement / Disagreement

Participants express differing views on the approach to calculating the expected arrival times, with some supporting the method of summing over possible events while others emphasize the conditional nature of the expectations based on the arrival times. The discussion remains unresolved with multiple competing views on the correct approach.

Contextual Notes

Participants acknowledge the complexity of the problem, particularly regarding the dependence on the number of events occurring in the interval [0-T] and the implications for calculating conditional expectations.

Mehmood_Yasir
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Assume a Poisson process with rate ##\lambda##.

Let ##T_{1}##,##T_{2}##,##T_{3}##,... be the time until the ##1^{st}, 2^{nd}, 3^{rd}##,...(so on) arrivals following exponential distribution. If I consider the fixed time interval ##[0-T]##, what is the expectation value of the arrival time ##1^{st}, 2^{nd}, 3^{rd}... ## i.e.,
1. ##E[T_{1}|T_{1}\le T]## ?
2. ##E[T_{2}|T_{1}<T_{2}\le T]## ?
3. ##E[T_{3}|T_{2}<T_{3}\le T]## ?
My approach! For Poisson process with rate ##\lambda##, each time interval corresponds to a random variable ##X_i## with an exponeitial distribution.Therefore,
\begin{align*}
&T_1=X_1 \\&
T_2=X_1+X_2\\&T_3=X_1+X_2+X3\\&...
\end{align*}
##T_i## has Gamma distribuiotn ##\Gamma(i,\lambda)##. If ##T## is a deterministic value not a random variable. Then, ##E[T_{1}|T_{1}\le T]##
\begin{align*}
E[T_{1}|T_{1}\le T]&=\int_{0}^\infty t_1f_{T_1|T_1 \le T}(t_1)dt_1\\&=\frac{1}{1-e^{-\lambda T}}\int_{0}^T t_1 \lambda e^{-\lambda t_1}dt_1\\&=\frac{-1}{1-e^{-\lambda T}}\int_0^T t_1de^{-\lambda t_1}\\&\text{(Final solution is )}\\&=\frac{-(Te^{-\lambda T}+\frac{1}{\lambda}e^{-\lambda T}-\frac{1}{\lambda})}{1-e^{-\lambda T}}
\end{align*}

What about ##E[T_{2}|T_{1}<T_{2}\le T]## and ##E[T_{3}|T_{2}<T_{3}\le T]##.
Can someone please guide me? I thank in advance.
 
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I think this is valid:
Suppose there are exactly m events in [0,T]. The probability of that is PT,m=##\frac{(\lambda T)^m}{m!}e^{-\lambda T}##.
For n≤m, the expected time to the nth of them is ##E[n,m,T]=\frac{nT}{m+1}##. The expected time over all values of m is then ##\frac{\Sigma _{m≥n}E[n,m,T]P_{T,m}}{\Sigma _{m≥n} P_{T,m}}##.

As a check, for large n that approximates ##\frac{nT}{n+1}##, as it should.
 
@haruspex many thanks for your answer. I tried to understand it but could not get it completely. Actually we don't know the no. of events in time ##[0-T]##.
Let me put this way. E.g., assume an arrival appear at ##t=0## and starts a clock for a duration of Time ##T##. Now the rest of the arrivals follow poisson process with rate ##\lambda##. When clock time which is ##T## expires, we have to calculate now the expected arrival time of the first, second and third,...so on.
I did for the first arrival which is in fact conditional expectation value of the arrival time i.e., ##E[T_{1}|T_{1}<=T]##.

Since the expected value of the arrival time of the second arrival will be greater than the arrival time of the first arrival and will be less than ##T##. Is this approach CORRECT analogous to my first proposal for determining value of the ##E[T_{2}|T_{1}<T_{2}<=T]## (see the attached image)?
image.png
 

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Mehmood_Yasir said:
Actually we don't know the no. of events in time [0−T]
I understand that. If you look at my final expression you will see it sums over all m (total number of events in T) ≥ n.
 
Last edited:

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