MHB Help in determining the type of distribution

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The discussion centers on identifying the type of distribution for a queue of requests that arrive at varying rates throughout the day. Participants explore whether the situation can be modeled as a Poisson process, noting that a Poisson process assumes a constant average rate of arrival, which may not apply here due to the fluctuating request rates. The conversation highlights the need to consider alternative distributions that account for the non-uniform arrival rates, such as a non-homogeneous Poisson process or other queuing models. Additionally, the importance of analyzing the specific arrival patterns and time intervals is emphasized to determine the most suitable distribution. Understanding the correct distribution is crucial for optimizing queue management and service efficiency.
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I have a queue of request that every during a day some requests arrive in a queue to be served. but, the rate of request's arrival is different in each hour.
I would appreciate that if somebody tells me what kind of distribution the problem is ?
 
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Re: help in determine what kind of Distribution is that

Why is it not still a Poisson Process?
 

Thread 'Hypothesis testing: Defining H0, HA hypotheses so that ( H_A)_A' makes sense'

The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...
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