Generating Function for Selecting Candies with Varying Quantities and Types

In summary, the author is trying to solve a problem involving candy and cups, but the problem is very complicated and the author does not understand it.
  • #1
toothpaste666
516
20

Homework Statement



given one each of u types of candy, two each of v types of candy, and three each of of w types of candy, find a generating function for the number of ways to select r candies.

The Attempt at a Solution



I am not sure if I understand this correctly, but this is what I came up with

(x^0 + x^1)^u (x^0 + x^1 + x^2)^v (x^0 + x^1 + x^2 + x^3)^w
 
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  • #2
What do you mean by a 'generating function'? Is it a probability generating function? If so, what is the random variable to which the function is being related?

If it's not a prob-gen function, then what does the 'x' in the above equation represent?

I'm pretty sure that, whatever the intended meaning of your expression, it won't be the answer, as it doesn't use r.

Regarding the meaning of the question itself, I think it's clear enough. Say the candy is arranged in u+v+w cups in a line in front of you. The first u cups each have one candy in, the next v cups have two each and the last w have three each. The candies in the k-th cup all have the number k written on them. You choose r candies from the cups and thus end up with a bunch of r numbers, some of which may be the same. The question is how many different collections of numbers can you get?

Although the question is clear, solving it doesn't seem easy. The answer will be an expression in terms of u, v, w and r. I imagine there's a standard distribution for this sort of thing. I thought maybe hypergeometric, but on a quick consideration, it didn't seem to fit. I can write it as a rather long, messy expression with multiple nested sums. There may be a slicker way though.
 
  • #3
It is not a probability generating function. This for a combinatorics class. The chapter is called "generating function models" and for this question we don't have to solve the problem, we only have to model it with a "generating function". The reason r is not included in the problem is because the answer would be the number of the coefficient of x^r when the expression is multiplied out (I am pretty sure)
 
  • #4
I see. Well in that case your solution is correct!
 
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  • #5
I find this chapter to be very abstract and confusing :/
 

What is a Generating Function Model?

A Generating Function Model is a mathematical tool used in statistics and probability theory to represent a probability distribution as a function. It is a type of power series that can be used to calculate the probability of certain outcomes in a given system.

How is a Generating Function Model used in statistical analysis?

Generating Function Models are commonly used in statistical analysis to simplify complex probability distributions and make calculations easier. They are particularly useful for analyzing systems with a large number of possible outcomes, such as in genetics or economics.

What are the advantages of using a Generating Function Model?

One of the main advantages of a Generating Function Model is that it allows for efficient calculation of probabilities for a large number of outcomes. It also allows for easier manipulation and analysis of complex probability distributions. Additionally, Generating Function Models can be used to model a variety of different systems and can be adapted to fit specific needs.

Are there any limitations to using a Generating Function Model?

While Generating Function Models can be useful, they do have some limitations. One of the main limitations is that they are not always suitable for modeling continuous distributions, as they are based on discrete outcomes. Additionally, Generating Function Models may not accurately represent all aspects of a system and may require some simplifications or assumptions.

How can I learn more about Generating Function Models?

There are many resources available for learning about Generating Function Models, including textbooks, online courses, and academic papers. It is also helpful to have a strong understanding of calculus and probability theory before diving into the topic. Consulting with a statistician or attending a workshop or conference on generating functions can also provide valuable insights.

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