Partitioning Generating Functions

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In summary, the problem is to find a generating function for the number of ways to distribute r identical objects into 3 indistinguishable boxes, and the issue of "indistinguishable boxes" means that order does not matter in terms of what goes into the boxes. However, the question may be misplaced in the book and cannot be solved at this time.
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Shoney45
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Homework Statement



Finda generating function for the number of ways to distribute r identical objects into 3 indistinguishable boxes.

Homework Equations





The Attempt at a Solution



It is the problem of "indistinguishable boxes" that has me flummoxed. I know that if the boxes were distinct, then my generating function would be:

(1 + x + x^2 + x^3 +...)^3

But I am not sure what to do with the matter of "indistinguishable boxes".
 
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  • #2
The only thing I can come up with is that order doesn't matter in terms of what goes into the boxes. In other words, if I am partitioning the integer 5 into 2,2,1...and I put each of those integers into one each of my three boxes...then 2,2,1 is the same as 1,2,2.

I still can't figure out though how that pans out as an expression in a generating function.
 
  • #3
We just hit up our professor, and he said the question is misplaced in the book. He said we don't have enough material yet to solve this question. So forget about this question.
 

1. What is a partitioning generating function?

A partitioning generating function is a mathematical tool used to represent the number of ways in which a set can be partitioned or divided into smaller subsets. It is a polynomial function where the coefficient of the term x^n represents the number of ways to partition a set of size n.

2. How is a partitioning generating function different from a regular generating function?

A partitioning generating function differs from a regular generating function in that it takes into account the number of ways in which a set can be partitioned, rather than just the number of subsets that can be created. This allows for a more detailed analysis of sets and their partitions.

3. What are the applications of partitioning generating functions?

Partitioning generating functions have various applications in combinatorics, probability, and statistics. They can be used to solve problems related to counting, sampling, and analyzing data sets. They are also commonly used in the field of computer science to analyze algorithms and data structures.

4. How are partitioning generating functions calculated?

Partitioning generating functions are calculated using the multiplication principle and the binomial theorem. The multiplication principle states that the total number of ways to partition a set is equal to the product of the number of ways to partition each element in the set. The binomial theorem is then used to expand the resulting polynomial function.

5. Can partitioning generating functions be used for infinite sets?

No, partitioning generating functions can only be used for finite sets. This is because the number of ways to partition an infinite set would be infinite as well, making it impossible to represent using a polynomial function. However, certain techniques such as generating function transformations can be used to extend the concept to countably infinite sets.

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