Poisson Process Conditional Distribution

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Homework Help Overview

The discussion revolves around finding the conditional cumulative distribution function (CDF) of a Poisson process, specifically F_X_t|X_t+Y_t=n(x), where X_t and Y_t are Poisson processes with rates a and b. The problem involves understanding the relationship between these processes and their joint distributions.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the use of conditional probability definitions and express uncertainty about their steps in deriving the CDF. There are questions about the notation used and the correctness of the approach taken towards the solution.

Discussion Status

Some participants have provided guidance on the notation and definitions, suggesting that the standard definition of a CDF should be used. There is an ongoing exploration of the problem, with no explicit consensus reached regarding the correctness of the current approaches.

Contextual Notes

Participants note the importance of using appropriate notation for counting processes and the distinction between '≤' and '<' in the context of CDFs. There is an acknowledgment of the potential confusion arising from the definitions and assumptions involved in the problem.

jiml
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Homework Statement


[itex]X_t[/itex] and [itex]Y_t[/itex] are poisson processes with rates [itex]a[/itex] and [itex]b[/itex]

[itex]n = 1,2,3...[/itex]Find the CDF [itex]F_X{}_t{}_|{}_X{}_t{}_+{}_Y{}_t{}_={}_n(x)[/itex]

Homework Equations


The Attempt at a Solution


[itex]F_X{}_t{}_|{}_X{}_t{}_+{}_Y{}_t{}_={}_n(x)[/itex]

[itex]=P(X_t<x|X_t+Y_t=n)[/itex]

[itex]=\frac{P(X_t<x,X_t+Y_t=n)}{P(X_t+Y_t=n)}[/itex]

Not sure from here, but here goes:

[itex]=\frac{P(Y_t>n-x)}{P(X_t+Y_t=n)}[/itex]

[itex]=1-\frac{P(Y_t<=n-x)}{P(X_t+Y_t=n)}[/itex]
Not sure if doing correctly.
 
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jiml said:

Homework Statement


[itex]X_t[/itex] and [itex]Y_t[/itex] are poisson processes with rates [itex]a[/itex] and [itex]b[/itex]

[itex]n = 1,2,3...[/itex]


Find the CDF [itex]F_X{}_t{}_|{}_X{}_t{}_+{}_Y{}_t{}_={}_n(x)[/itex]


Homework Equations





The Attempt at a Solution


[itex]F_X{}_t{}_|{}_X{}_t{}_+{}_Y{}_t{}_={}_n(x)[/itex]

[itex]=P(X_t<x|X_t+Y_t=n)[/itex]

[itex]=\frac{P(X_t<x,X_t+Y_t=n)}{P(X_t+Y_t=n)}[/itex]

Not sure from here, but here goes:

[itex]=\frac{P(Y_t>n-x)}{P(X_t+Y_t=n)}[/itex]

[itex]=1-\frac{P(Y_t<=n-x)}{P(X_t+Y_t=n)}[/itex]



Not sure if doing correctly.

Since X and Y are counting processes, you should probably avoid using the letter 'x' for values of them, so instead, should use something like ##F_{X_t|X_t + Y_t = n}(m).## Note also that the standard definition of a cdf involves '≤', not '<', so
[tex]F_{X_t|X_t + Y_t = n}(m) = P(X_t \leq m|X_t+Y_t = n).[/tex]
 
Can someone please help me with my solution, whether I am on the right track in my steps to get to a solution. Thanks
 
jiml said:
Can someone please help me with my solution, whether I am on the right track in my steps to get to a solution. Thanks

All you have done is use the definition of conditional probability; you are nowhere near the final solution.
 
ok,thanks
 
Last edited:

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