Value of t for Probability Generating Function

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SUMMARY

The discussion centers on the interpretation of the Probability Generating Function (PGF) for a uniform distribution, specifically the function defined as ##G_X(t)=\frac{t(1-t^n)}{n(1-t)}##. It clarifies that while ##G_X(1)## is often stated as 1, this is not universally correct; instead, the limit ##G(1−) = 1## must be considered. Additionally, the value of ##G_X(2)## represents the expectation value of 2x, though its significance is context-dependent.

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songoku
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TL;DR
Let PGF be

$$G_X (t) = E(t^x) = \Sigma P(X=x_i) t^{x_i}$$

and ##G_X (1) = 1##
My questions:

1) What about if t = 2? Is there a certain meaning to ##G_X (2)## ?

2) PGF for uniform distribution is ##G_X (t)=\frac{t(1-t^n)}{n(1-t)}## and for t = 1 ##G_X (1)## is undefined so ##G_X (1) =1## is not true for all cases?

Thanks
 
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GX(1) = 1 is not strictly correct. The condition is (to quote Wikipedia)
" G(1−) = 1, where G(1−) = limz→1G(z) from below, since the probabilities must sum to one. "
 
mjc123 said:
GX(1) = 1 is not strictly correct. The condition is (to quote Wikipedia)
" G(1−) = 1, where G(1−) = limz→1G(z) from below, since the probabilities must sum to one. "

What about ##G_X (2)## ? Is there a certain meaning to it?

Thanks
 
It is the expectation value of 2x. Whether that is particularly meaningful is another question.
 
mjc123 said:
It is the expectation value of 2x. Whether that is particularly meaningful is another question.
So whether it is meaningful or not depend on the context being considered so it will be more like case-by-case basis?

Thanks
 

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