Cannot tell when a probability generating function converges for |s|<1

This is not possible, so the function is not a probability generating function.In summary, In summary, the conversation discusses the properties of a probability generating function and how to determine if a function is a probability generating function. The solution states that g(s)=1+s-s^2 is not a probability generating function because it violates the property that P(1) = 1. The conversation also mentions other functions that are and are not probability generating functions and suggests that P(1) should equal the sum of the probabilities for all possible outcomes.
  • #1
juanma101285
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Hi, I have a problem that is already solved... I thought 3 of the 4 functions were probability generating functions, but I got one wrong and don't know why.

The solution says [itex]g(s)=1+s-s^2[/itex] is not a probability generating function. However, g(1)=1 and I think g(s) converges to 1 for |s|<1. Isn't that correct? If so, what is it that invalidates this function as a probability generating function?

The solution says that [itex]g(s)=(1/3)*(1+s+s^4)[/itex] and [itex]g(s)=(2-s^2)^{-1}[/itex] are prob. gen. functions and that [itex]g(s)=1+s-s^2[/itex] and [itex]g(s)=(1/2)(1+s+s^3)[/itex] are not (I know the last one is not because g(1)=3/2).

Thanks a lot for your help! :) And if you could also give me an explanation of other things I need to look for in a function to tell if it is a p.g.f., I would really appreciate that.
 
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  • #2
If [itex]1 + s - s^2[/itex] were a probability generating function, then we would have [itex]P(2) = -1[/itex].
 

FAQ: Cannot tell when a probability generating function converges for |s|<1

1. What is a probability generating function?

A probability generating function is a mathematical tool used to describe the probability distribution of a discrete random variable.

2. How is a probability generating function different from a probability density function?

A probability generating function is used for discrete random variables, while a probability density function is used for continuous random variables.

3. What does it mean for a probability generating function to converge?

When a probability generating function converges, it means that it approaches a finite value as the input variable increases without bound. In other words, the function stabilizes and does not continue to change significantly with increasing input values.

4. Why is it important to know when a probability generating function converges?

Knowing when a probability generating function converges is important because it indicates that the probability distribution of a random variable has a well-defined shape and can be described accurately by the function. This can help in making predictions and analyzing data.

5. What happens when a probability generating function does not converge for |s|<1?

If a probability generating function does not converge for |s|<1, it means that the function does not have a well-defined shape and cannot accurately describe the probability distribution of the random variable. This may indicate that the data being analyzed is not appropriate for a probability generating function or that the function needs to be modified.

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