Probability generating function.

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SUMMARY

The discussion centers on the probability generating function (PGF) for integer-valued random variables (RVs). It establishes that the summation from n=0 to infinity of s^n P(X≤n) can be expressed as (1-s)^-1 multiplied by the summation from k=0 to infinity of P(X=k)s^k. The transformation of the double sum into a single sum using k as the primary index is crucial for deriving the correct result, confirming the relationship between PGFs and cumulative distribution functions.

PREREQUISITES
  • Understanding of probability theory and random variables
  • Familiarity with generating functions
  • Knowledge of summation techniques in mathematical analysis
  • Basic calculus for manipulating infinite series
NEXT STEPS
  • Study the properties of probability generating functions in detail
  • Explore the relationship between PGFs and moment generating functions
  • Learn about convergence criteria for infinite series
  • Investigate applications of PGFs in combinatorial problems
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Mathematicians, statisticians, and students studying probability theory, particularly those interested in the applications of generating functions in statistical analysis and combinatorics.

nikki92
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For any integer valued RV X Summation n=0 to infinity of s^n P(X=<n) = (1-s)^-1 * Summation k=0 to infinity of P(x=k)s^k


Why does Sum k=0 to infinity P(x=k)s^k = sum n=0 to infinity of P(X=< n)
 
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$$\sum_{n=0}^{\infty} s^n P(X\leq n) = \sum_0^{\infty} s^n \sum_{k=0}^n P(X=k)$$
You can re-write this double sum and use k as primary index. The inner sum (over n) has an explicit formula then, and you get the correct result.
 

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