In mathematics, the term generating function is used to describe an infinite sequence of numbers (an) by treating them as the coefficients of a series expansion. The sum of this infinite series is the generating function. Unlike an ordinary series, this formal series is allowed to diverge, meaning that the generating function is not always a true function and the "variable" is actually an indeterminate. Generating functions were first introduced by Abraham de Moivre in 1730, in order to solve the general linear recurrence problem. One can generalize to formal series in more than one indeterminate, to encode information about arrays of numbers indexed by several natural numbers.
Contents
- Definitions
- Ordinary generating function
- Exponential generating function
- Poisson generating function
- Lambert series
- Bell series
- Dirichlet series generating functions
- Polynomial sequence generating functions
- Ordinary generating functions
- Rational functions
- Multiplication yields convolution
- Relation to discrete time Fourier transform
- Asymptotic growth of a sequence
- Asymptotic growth of the sequence of squares
- Asymptotic growth of the Catalan numbers
- Bivariate and multivariate generating functions
- Properties of the h t h displaystyle hth convergent functions
- Mathematica code to find parameters for the J fractions generating a sequence
- Examples
- Dirichlet series generating function
- Multivariate generating function
- Techniques of evaluating sums with generating function
- Convolution
- Free parameter
- Other Applications
- Other generating functions
- History
- References
There are various types of generating functions, including ordinary generating functions, exponential generating functions, Lambert series, Bell series, and Dirichlet series; definitions and examples are given below. Every sequence in principle has a generating function of each type (except that Lambert and Dirichlet series require indices to start at 1 rather than 0), but the ease with which they can be handled may differ considerably. The particular generating function, if any, that is most useful in a given context will depend upon the nature of the sequence and the details of the problem being addressed.
Generating functions are often expressed in closed form (rather than as a series), by some expression involving operations defined for formal series. These expressions in terms of the indeterminate x may involve arithmetic operations, differentiation with respect to x and composition with (i.e., substitution into) other generating functions; since these operations are also defined for functions, the result looks like a function of x. Indeed, the closed form expression can often be interpreted as a function that can be evaluated at (sufficiently small) concrete values of x, and which has the formal series as its series expansion; this explains the designation "generating functions". However such interpretation is not required to be possible, because formal series are not required to give a convergent series when a nonzero numeric value is substituted for x. Also, not all expressions that are meaningful as functions of x are meaningful as expressions designating formal series; for example, negative and fractional powers of x are examples of functions that do not have a corresponding formal power series.
Generating functions are not functions in the formal sense of a mapping from a domain to a codomain. Generating functions are sometimes called generating series, in that a series of terms can be said to be the generator of its sequence of term coefficients.
Definitions
A generating function is a device somewhat similar to a bag. Instead of carrying many little objects detachedly, which could be embarrassing, we put them all in a bag, and then we have only one object to carry, the bag.—George Polya, Mathematics and plausible reasoning (1954)A generating function is a clothesline on which we hang up a sequence of numbers for display.—Herbert Wilf, Generatingfunctionology (1994)Ordinary generating function
The ordinary generating function of a sequence an is
When the term generating function is used without qualification, it is usually taken to mean an ordinary generating function.
If an is the probability mass function of a discrete random variable, then its ordinary generating function is called a probability-generating function.
The ordinary generating function can be generalized to arrays with multiple indices. For example, the ordinary generating function of a two-dimensional array am, n (where n and m are natural numbers) is
Exponential generating function
The exponential generating function of a sequence an is
Exponential generating functions are generally more convenient than ordinary generating functions for combinatorial enumeration problems that involve labelled objects.
Poisson generating function
The Poisson generating function of a sequence an is
Lambert series
The Lambert series of a sequence an is
Note that in a Lambert series the index n starts at 1, not at 0, as the first term would otherwise be undefined.
Bell series
The Bell series of a sequence an is an expression in terms of both an indeterminate x and a prime p and is given by
Dirichlet series generating functions
Formal Dirichlet series are often classified as generating functions, although they are not strictly formal power series. The Dirichlet series generating function of a sequence an is
The Dirichlet series generating function is especially useful when an is a multiplicative function, in which case it has an Euler product expression in terms of the function's Bell series
If an is a Dirichlet character then its Dirichlet series generating function is called a Dirichlet L-series.
Polynomial sequence generating functions
The idea of generating functions can be extended to sequences of other objects. Thus, for example, polynomial sequences of binomial type are generated by
where pn(x) is a sequence of polynomials and f(t) is a function of a certain form. Sheffer sequences are generated in a similar way. See the main article generalized Appell polynomials for more information.
Ordinary generating functions
Polynomials are a special case of ordinary generating functions, corresponding to finite sequences, or equivalently sequences that vanish after a certain point. These are important in that many finite sequences can usefully be interpreted as generating functions, such as the Poincaré polynomial and others.
A key generating function is that of the constant sequence 1, 1, 1, 1, 1, 1, 1, 1, 1, ..., whose ordinary generating function is
The left-hand side is the Maclaurin series expansion of the right-hand side. Alternatively, the right-hand side expression can be justified by multiplying the power series on the left by 1 − x, and checking that the result is the constant power series 1, in other words that all coefficients except the one of x0 vanish. Moreover, there can be no other power series with this property. The left-hand side therefore designates the multiplicative inverse of 1 − x in the ring of power series.
Expressions for the ordinary generating function of other sequences are easily derived from this one. For instance, the substitution x → ax gives the generating function for the geometric sequence 1, a, a2, a3, ... for any constant a:
(The equality also follows directly from the fact that the left-hand side is the Maclaurin series expansion of the right-hand side.) In particular,
One can also introduce regular "gaps" in the sequence by replacing x by some power of x, so for instance for the sequence 1, 0, 1, 0, 1, 0, 1, 0, .... one gets the generating function
By squaring the initial generating function, or by finding the derivative of both sides with respect to x and making a change of running variable n → n-1, one sees that the coefficients form the sequence 1, 2, 3, 4, 5, ..., so one has
and the third power has as coefficients the triangular numbers 1, 3, 6, 10, 15, 21, ... whose term n is the binomial coefficient
More generally, for any non-negative integer k and non-zero real value a, it is true that
Note that, since
one can find the ordinary generating function for the sequence 0, 1, 4, 9, 16, ... of square numbers by linear combination of binomial-coefficient generating sequences;
Rational functions
The ordinary generating function of a sequence can be expressed as a rational function (the ratio of two polynomials) if and only if the sequence is a linear recursive sequence with constant coefficients; this generalizes the examples above. Going in the reverse direction, every sequence generated by a fraction of polynomials satisfies a linear recurrence with constant coefficients; these coefficients are identical to the coefficients of the fraction denominator polynomial (so they can be directly read off).
Multiplication yields convolution
Multiplication of ordinary generating functions yields a discrete convolution (the Cauchy product) of the sequences. For example, the sequence of cumulative sums
of a sequence with ordinary generating function G(an; x) has the generating function
because 1/(1-x) is the ordinary generating function for the sequence (1, 1, ...).
Relation to discrete-time Fourier transform
When the series converges absolutely,
is the discrete-time Fourier transform of the sequence a0, a1, ....
Asymptotic growth of a sequence
In calculus, often the growth rate of the coefficients of a power series can be used to deduce a radius of convergence for the power series. The reverse can also hold; often the radius of convergence for a generating function can be used to deduce the asymptotic growth of the underlying sequence.
For instance, if an ordinary generating function G(an; x) that has a finite radius of convergence of r can be written as
where each of A(x) and B(x) is a function that is analytic to a radius of convergence greater than r (or is entire), and where B(r) ≠ 0 then
using a multiset coefficient, a binomial coefficient, or the Gamma function.
Often this approach can be iterated to generate several terms in an asymptotic series for an. In particular,
The asymptotic growth of the coefficients of this generating function can then be sought via the finding of A, B, α, β, and r to describe the generating function, as above.
Similar asymptotic analysis is possible for exponential generating functions. With an exponential generating function, it is an/n! that grows according to these asymptotic formulae.
Asymptotic growth of the sequence of squares
As derived above, the ordinary generating function for the sequence of squares is
With r = 1, α = 0, β = 3, A(x) = 0, and B(x) = x(x+1), we can verify that the squares grow as expected, like the squares:
Asymptotic growth of the Catalan numbers
The ordinary generating function for the Catalan numbers is
With r = 1/4, α = 1, β = −1/2, A(x) = 1/2, and B(x) = −1/2, we can conclude that, for the Catalan numbers,
Bivariate and multivariate generating functions
One can define generating functions in several variables for arrays with several indices. These are called multivariate generating functions or, sometimes, super generating functions. For two variables, these are often called bivariate generating functions.
For instance, since
the generating function for the binomial coefficients is:
Definitions
Expansions of (formal) Jacobi-type and Stieltjes-type continued fractions (J-fractions and S-fractions, respectively) whose
The coefficients of
where
Properties of the h t h {displaystyle h^{th}} convergent functions
For
component-wise through the sequences,
Moreover, the rationality of the convergent function,
for non-symbolic, determinate choices of the parameter sequences,
Mathematica code to find parameters for the J-fractions generating a sequence
For any prescribed, desired sequence of the
Examples
The next table provides examples of closed-form formulas for the component sequences found computationally (and subsequently proved correct in the cited references ) in several special cases of the prescribed sequences,
Note that the radii of convergence of these series corresponding to the definition of the Jacobi-type J-fractions given above are in general different from that of the corresponding power series expansions defining the ordinary generating functions of these sequences.
Examples
Generating functions for the sequence of square numbers an = n2 are:
Ordinary generating function
Exponential generating function
Bell series
Dirichlet series generating function
using the Riemann zeta function.
The sequence an generated by a Dirichlet series generating function corresponding to:
where
Multivariate generating function
Multivariate generating functions arise in practice when calculating the number of contingency tables of non-negative integers with specified row and column totals. Suppose the table has r rows and c columns; the row sums are
in
Techniques of evaluating sums with generating function
Generating functions give us several methods to manipulate sums and to establish identities between sums.
The simplest case occurs when
For example, we can manipulate
and thus
Using
which can also be written as
Convolution
1.Consider A(z) and B(z) are ordinary generating functions.2.Consider A(z) and B(z) are exponential generating functions.Free parameter
Sometimes the sum
Both methods discussed so far have
For example, if we want to compute
we can treat
Interchanging summation (“snake oil”) gives
Now the inner sum is
Then we obtain
Other Applications
Generating functions are used to:
Other generating functions
Examples of polynomial sequences generated by more complex generating functions include:
Other sequences generated by more complex generating functions:
History
George Polya writes in Mathematics and plausible reasoning:
The name "generating function" is due to Laplace. Yet, without giving it a name, Euler used the device of generating functions long before Laplace [..]. He applied this mathematical tool to several problems in Combinatory Analysis and the Theory of Numbers.