# 3. Combinatorial Parameters and Multivariate Generating Functions

## III.1 An introduction to bivariate generating functions (BGFs)

## III.2 Bivariate generating functions and probability distributions

## III.3 Inherited parameters and ordinary MGFs

## III.4 Inherited parameters and exponential MGFs

## III.5 Recursive parameters

## III.6 Complete generating functions and discrete models

## III.7 Additional constructions

## III.8 Extremal parameters

## III.9 Perspective

#### Selected Exercises

## Note III.17

*Leaves and node-degree profile in Cayley trees.*For Cayley trees, the bivariate EGF with $u$ marking the number of leaves is the solution to $$T(z,u)=uz+z(e^{T(z,u)}-1).$$ (By Lagrange inversion, the distribution is expressible in terms of Stirling partition numbers.) The mean number of leaves in a random Cayley tree is asymptotic to $ne^{-1}$. More generally, the mean number of nodes of outdegree $k$ in a random Cayley tree of size~$n$ is asymptotic to $$n\cdot e^{-1}\, {1\over k!}.$$ Degrees are thus approximately described by a Poisson law of rate 1.

## Note III.21

*After Bhaskara Acharya (circa 1150 AD).*Consider all the numbers formed in decimal with digit 1 used once, with digit 2 used twice, ..., with digit 9 used nine times. Such numbers all have 45 digits. Compute their sum $S$ and discover, much to your amazement that $S$ equals

`45875559600006153219084769286399999999999999954124440399993846780915230713600000.`This number has a long run of nines (and further nines are hidden!). Is there a simple explanation? This exercise is inspired by the Indian mathematician Bhaskara Acharya who discovered multinomial coefficients near 1150 AD.

#### Selected Experiments

## Program III.1

Write a program that generates 1000 random permutations of size $N$ for $N$ = $10^3$, $10^4$, ... (going as far as you can) and plots the distribution of the number of cycles, validating that the mean is concentrated at $H_N$.#### Web Exercises

## III.1

(Exercise 5.13 in*Analysis of Algorithms*) What is the average number of 1 bits in a random bitstring of length $N$ having no 00?

## III.2

(E. Neyman) Define the cost of a ternary (base 3) string to be the sum of its digits. Derive an OBGF for ternary strings with this cost, and use it to compute the average cost of an $N$-digit string.

## III.3

(D. Mavrides) Derive an OBGF for the number of 1s in the set of ordered partitions of an integer, and use it to compute the expected number of 1s in a randomly selected partition of $N$.

## III.4

(M. Bahrani) A*run*in a bitstring is a maximal sequence of consecutive identical bits. For example, the string 11010100001 has 7 runs, with lengths 2, 1, 1, 1, 1, 4, 1 respectively. What is the average number of runs in a random binary string of length $N$? List the corresponding horizontal and vertical OBGFs. Is the distribution of the number of runs in binary strings concentrated?

## III.5

(T. Ratigan) Derive a combinatorial construction leading to an equation involving the OBGF for the number of vertices of degree $d$ in a Catalan tree with $n$ node Solve the equation for $d=1$ and give an asymptotic estimate of the number of degree-1 nodes in a random $n$-node Catalan tree.

## III.6

(M. Tyler) Define the*unit $n$-hypercube*to be the set of points $[0,1]^n \subset \mathbb{R}^n$. For example, the unit 0-hypercube is a point, and the unit 3-hypercube is the unit cube. Define a

*$k$-face*of the unit $n$-hypercube to be a copy of the $k$-hypercube in the exterior of the $n$-hypercube. More formally, a $k$-face of the unit $n$-hypercube is a set of the form $\prod_{1\le i\le n}S_i$ where $S_i$ is either $\{0\}$, $\{1\}$, or $[0, 1]$ for each $i$ between $1$ and $n$ and there are exactly $k$ indices $i$ such that $S_i = [0, 1]$. Derive a combinatorial construction leading to an OBGF and an explicit formula for the number of $k$-faces in the unit $n$-hypercube. Use the OBGF to derive the expected value of the dimension a random face of the unit $n$-hypercube.