Fact-checked by Grok 2 weeks ago

Falling and rising factorials

Falling and rising factorials are functions that generalize the ordinary to arbitrary real or complex arguments, playing key roles in , calculus, and the theory of . The falling factorial of x to the power n, denoted (x)_n, is defined as the product x(x-1)(x-2)\cdots(x-n+1) for positive n, with (x)_0 = 1. The rising factorial, also known as the Pochhammer symbol and denoted x^{(n)} or (x)_n in some contexts, is defined as x(x+1)(x+2)\cdots(x+n-1), again with the base case 1 for n=0. The falling factorial coincides with the standard for positive n, as n! = (n)_n. The rising factorial satisfies n! = 1^{(n)}. The falling and rising factorials are closely related through the (x)_n = (-1)^n (-x)^{(n)}, which highlights their and allows interconversion in analytic expressions. Both can be expressed using the for non-integer extensions: the rising factorial satisfies x^{(n)} = \frac{\Gamma(x+n)}{\Gamma(x)}, while the falling factorial follows analogously as (x)_n = \frac{\Gamma(x+1)}{\Gamma(x-n+1)}. Notation varies across literature; for instance, the Pochhammer symbol (x)_n typically denotes the rising factorial in theory, but some texts use it for the falling version, necessitating caution. Basic properties include recurrence relations, such as (x)_{n+1} = x(x)_n - n(x)_n for the falling factorial, and similar forms for the rising one. In , falling factorials appear in the binomial theorem's generalization, (x+y)_n = \sum_{k=0}^n \binom{n}{k} (x)_k (y)_{n-k}, counting permutations and combinations with repetitions. Their is (1+t)^x = \sum_{k=0}^\infty \frac{(x)_k}{k!} t^k, linking them to exponential series. Rising factorials are essential in hypergeometric series expansions, where they parameterize confluent and generalized hypergeometric functions, such as {}_pF_q(a_1,\dots,a_p;b_1,\dots,b_q;z) = \sum_{k=0}^\infty \frac{(a_1)_k \cdots (a_p)_k}{(b_1)_k \cdots (b_q)_k} \frac{z^k}{k!}. In finite differences, falling factorials form a basis for analogous to powers, enabling discrete analogs of derivatives via forward differences \Delta (x)_n = n (x)_{n-1}. These applications extend to statistics for modeling regressions and in for and splines.

Definitions and Notation

Falling Factorial

The falling factorial, denoted (x)_n, is a in x of n defined for any real or x and non-negative n. It extends the concept of the ordinary from positive integers to broader domains and appears frequently in , , and . For n \geq 1, the falling factorial is given by the product (x)_n = x(x-1)(x-2) \cdots (x-n+1), which consists of n successive terms decreasing by 1 starting from x. For n=0, the convention yields (x)_0 = 1. This definition aligns with the notation introduced in seminal works on , where the falling factorial serves as a basis for and finite differences. When x is a positive k with k \geq n, the falling factorial simplifies to the formula (k)_n = \frac{k!}{(k-n)!}, representing the number of ways to arrange n distinct items from k available ones, though here it is presented purely as an algebraic reduction. This special case connects directly to the ordinary k!, which is recovered when n = k as (k)_k = k!. The falling factorial also admits a recursive : (x)_n = (x)_{n-1} (x - n + 1) for n \geq 1, with the base case (x)_0 = 1. This recurrence facilitates computational evaluation and proofs involving the function. As a counterpart, the rising factorial employs a product of increasing terms, providing a perspective in related mathematical contexts.

Rising Factorial

The rising factorial, denoted x^{(n)} and also known as the Pochhammer symbol (x)_n, generalizes the factorial to real or arguments x and nonnegative integers n. It is defined by the ascending product x^{(n)} = x(x+1)(x+2) \cdots (x+n-1) for n \geq 1, with the base case x^{(0)} = 1. This construction emphasizes an increasing sequence of terms, in contrast to the falling factorial's decreasing sequence. When x is a positive , the rising factorial reduces to a ratio of s: x^{(n)} = \frac{(x+n-1)!}{(x-1)!}. This equivalence follows directly from the product form, as the terms x through x+n-1 form the upper portion of the expanded (x+n-1)! after canceling the lower terms up to (x-1)!. The rising factorial admits a recursive definition: x^{(n)} = x^{(n-1)} (x + n - 1), with x^{(0)} = 1, which mirrors the iterative multiplication in the product formula. For analytic extension beyond integers, the rising factorial connects to the : x^{(n)} = \frac{\Gamma(x+n)}{\Gamma(x)}, valid when x is not a non-positive to avoid poles in the . This relation, introduced by Leo August Pochhammer in the context of hypergeometric functions, enables evaluation for non-integer x and underpins its role in and series expansions.

Relation Between Falling and Rising

The falling factorial (x)_n and the rising factorial x^{(n)} are interconnected through identities that shift the argument or incorporate a sign change, allowing one to be expressed directly in terms of the other. A primary relation is given by the argument shift identity x^{(n)} = (x + n - 1)_n, which equates the product x(x+1)\cdots(x+n-1) for the rising factorial to the falling factorial starting at the raised base x + n - 1. The converse follows immediately as (x)_n = (x - n + 1)^{(n)}, reflecting the reverse ordering of factors in the products. Another fundamental link involves , with the identity (x)_n = (-1)^n (-x)^{(n)}, derived from expanding both sides and observing the sign pattern in the factors of the falling factorial at -x. This relation facilitates analytic continuations and handles cases with negative or arguments. Both factorials feature prominently in generalized expansions, where the falling factorial underlies the series for (1 + y)^x = \sum_{k=0}^\infty \binom{x}{k} y^k with \binom{x}{k} = (x)_k / k!, while the rising factorial appears in (1 - y)^{-x} = \sum_{k=0}^\infty \frac{x^{(k)}}{k!} y^k, linking them through argument adjustments like replacing y with -y and shifting x. The Pochhammer symbol (x)_n, standard for the rising factorial since its introduction by Leo August Pochhammer in studies of hypergeometric series, contrasts with falling factorial notation in contemporary texts, though earlier literature occasionally reversed these conventions.

Combinatorial Interpretations

Basic Examples

The falling factorial (x)_n and rising factorial x^{(n)} are defined as products of n consecutive terms, with the falling form decreasing from x and the rising form increasing from x. For integer values, consider x = 5 and n = 3: (5)_3 = 5 \times 4 \times 3 = 60, while $5^{(3)} = 5 \times 6 \times 7 = 210. These computations follow directly from the product definitions. For non-integer arguments, the definitions extend naturally. For example, with x = 1/2 and n = 2, \left(\frac{1}{2}\right)_2 = \frac{1}{2} \times \left(\frac{1}{2} - 1\right) = \frac{1}{2} \times \left(-\frac{1}{2}\right) = -\frac{1}{4}. The rising factorial in this case is \left(1/2\right)^{(2)} = (1/2) \times (3/2) = 3/4. When n = 0, both the falling and rising factorials equal 1 for any x, as they represent the empty product. The following table provides further computations for small integer values of x = 0, 1, 2, 3 and n = 1, 2, 3:
xn(x)_n (falling)x^{(n)} (rising)
0100
0200
0300
1111
1202
1306
2122
2226
23024
3133
32612
33660
These values are obtained by direct multiplication according to the product forms.

Binomial Coefficient Connections

The generalized \binom{x}{n} for real or x and nonnegative n is defined as \binom{x}{n} = \frac{(x)_n}{n!}, where (x)_n denotes the falling factorial. This definition extends the classical , which applies when x is a nonnegative , to arbitrary upper indices while preserving key algebraic properties. When x = k is a positive with k \geq n, the falling factorial (k)_n combinatorially interprets as the number of injections (one-to-one functions) from a set of n elements to a set of k elements, equivalent to the P(k, n) = k! / (k - n)!. Thus, \binom{k}{n} = (k)_n / n! counts the number of ways to choose n distinct elements from k and arrange them in order, divided by the n! arrangements to yield unordered combinations. For the rising factorial, the multichoose coefficient \binom{x + n - 1}{n}, which enumerates combinations with repetition (the number of ways to choose n items from x types allowing multiples), is given by \binom{x + n - 1}{n} = \frac{x^{(n)}}{n!}, where x^{(n)} is the rising factorial. This connection highlights the rising factorial's role in multisets and stars-and-bars theorems in . These binomial connections underpin the generalized , which states that for |y| < 1, (1 + y)^x = \sum_{n=0}^{\infty} \binom{x}{n} y^n = \sum_{n=0}^{\infty} \frac{(x)_n}{n!} y^n. This expansion, valid for non-integer x, relies on the falling factorial to generate the coefficients and converges within the specified radius. The theorem generalizes the finite binomial expansion for integer powers and appears in applications like generating functions and hypergeometric series.

Algebraic Properties

Fundamental Identities

Falling and rising factorials satisfy several core algebraic identities that facilitate their manipulation in combinatorial and analytical contexts. These identities stem from the product definitions and enable efficient computation and expansion of expressions involving them. One fundamental multiplication identity is \begin{equation} (x)_m (x - m)n = (x){m+n}, \end{equation} where (x)_k denotes the falling factorial. This relation arises because the product (x)_m consists of the terms x(x-1)\cdots(x-m+1), and multiplying by (x-m)_n = (x-m)(x-m-1)\cdots(x-m-n+1) extends the sequence consecutively to form the full falling factorial of length m+n. Another key identity is the addition or recurrence formula, \begin{equation} (x+1)_n = (x)n + n (x){n-1}, \end{equation} valid for nonnegative integers n, with the base case (x)_0 = 1. This equation mirrors the recursive structure of and serves as the basis for forward differences in , where the difference operator applied to the falling factorial yields \Delta (x)_n = n (x)_{n-1}. For example, when n=2, it confirms (x+1)_2 = (x+1)x = x(x-1) + 2x = (x)_2 + 2(x)_1. The falling factorial also admits a simple cancellation property, \begin{equation} \frac{(x)n}{(x){n-1}} = x - n + 1, \end{equation} for n \geq 1. This follows immediately from the product form, as (x)_n = (x)_{n-1} \cdot (x - n + 1), isolating the final term in the sequence. Such ratios are useful in deriving higher-order relations and normalizing expressions. A symmetry identity links the falling and rising factorials: \begin{equation} (x)_n = (x - n + 1)^{(n)}, \end{equation} where (y)^{(n)} = y(y+1)\cdots(y+n-1) is the rising factorial. Both sides represent the product of n consecutive terms centered around x - (n-1)/2, but in reverse order, ensuring equality. Equivalently, \begin{equation} (x)_n = (-1)^n (-x)^{(n)}, \end{equation} which interchanges the roles of falling and rising via negation and provides a duality useful in generating functions and special functions. For instance, with n=2, (x)_2 = x(x-1) and (x-1)^{(2)} = (x-1)x, confirming the match.

Properties for Real and Negative Arguments

The falling factorial (x)_n for positive integer n extends naturally to real or complex values of x via the gamma function: (x)_n = \frac{\Gamma(x+1)}{\Gamma(x-n+1)}, provided x - n + 1 is not a non-positive integer, where the gamma function \Gamma(z) is the meromorphic continuation of the factorial to the complex plane. This representation preserves the product form for positive integer x > n - 1 while enabling evaluation at non-integer points. For negative orders, let n = -m with m a positive integer. The gamma extension yields (x)_{-m} = \frac{\Gamma(x+1)}{\Gamma(x + m + 1)} = \frac{1}{(x+1)^{(m)}}, where (y)^{(m)} = y(y+1) \cdots (y + m - 1) denotes the rising factorial (Pochhammer symbol). This establishes an inverse relation between falling factorials of order -m and rising factorials of order m. The extended falling factorial exhibits singularities corresponding to the poles of the gamma function in the denominator. For positive integer n, poles occur when x - n + 1 = 0, -1, -2, \dots, that is, when x = n-1, n-2, n-3, \dots—specifically at non-positive integers x \leq n-1. For negative orders n = -m, poles arise in the denominator \Gamma(x + m + 1) when x + m + 1 = 0, -1, -2, \dots, or x = -m-1, -m-2, \dots, again at non-positive integers x in relevant ranges. These singularities reflect the analytic continuation's limitations near points where the original product definition breaks down. As an illustrative example, consider (-1/2)_3: (-1/2)_3 = \frac{\Gamma(1/2)}{\Gamma(-1/2 - 3 + 1)} = \frac{\Gamma(1/2)}{\Gamma(-5/2)}. Using \Gamma(1/2) = \sqrt{\pi} and the recurrence \Gamma(z) = \Gamma(z+1)/z applied iteratively, \Gamma(-5/2) = \frac{\Gamma(-3/2)}{-5/2} = \frac{\Gamma(-1/2)/(-3/2)}{-5/2} = \frac{\Gamma(1/2)/(-1/2 \cdot -3/2)}{-5/2} = -\frac{8}{15} \sqrt{\pi}, yielding (-1/2)_3 = \frac{\sqrt{\pi}}{-8/15 \sqrt{\pi}} = -\frac{15}{8}. This computation demonstrates the extension's ability to produce rational (fractional) values for non- negative arguments, distinct from the integer cases.

Calculus and Difference Equations

Derivatives and Integrals

The derivative of the falling factorial (x)_n can be obtained by applying the to its definition as (x)_n = \prod_{k=0}^{n-1} (x - k). Since the derivative of each factor x - k is 1, the Leibniz rule for the product of n functions yields \frac{d}{dx} (x)_n = \sum_{k=0}^{n-1} \prod_{\substack{j=0 \\ j \neq k}}^{n-1} (x - j). Each term in the sum is the full product divided by the omitted factor, so \prod_{j \neq k} (x - j) = (x)_n / (x - k), giving \frac{d}{dx} (x)_n = (x)_n \sum_{k=0}^{n-1} \frac{1}{x - k}. This sum equals the difference of harmonic numbers for positive integer arguments x \geq n, specifically H_x - H_{x-n}, where H_m = \sum_{i=1}^m 1/i. For general real or complex arguments (with appropriate via the ), the sum is the difference of digamma functions: \psi(x+1) - \psi(x - n + 1), where \psi(z) = \Gamma'(z)/\Gamma(z). Thus, \frac{d}{dx} (x)_n = (x)_n \left[ \psi(x+1) - \psi(x - n + 1) \right]. Similarly, the rising factorial x^{(n)} = \prod_{k=0}^{n-1} (x + k) has derivative \frac{d}{dx} x^{(n)} = x^{(n)} \sum_{k=0}^{n-1} \frac{1}{x + k} = x^{(n)} \left[ \psi(x + n) - \psi(x) \right], again using the difference for the sum, with the case following from harmonic numbers via H_{x+n-1} - H_{x-1}. As a of degree n, the falling factorial (x)_n has an antiderivative that is also a of degree n+1. For small n, explicit forms are straightforward. For n=1, (x)_1 = x and \int (x)_1 \, dx = \frac{x^2}{2} + C. For n=2, (x)_2 = x(x-1) = x^2 - x and \int (x)_2 \, dx = \frac{x^3}{3} - \frac{x^2}{2} + C. In general, the antiderivative can be expressed recursively or in terms of the {}_2F_1, reflecting the nature and connections to , though explicit closed forms beyond low n are typically expressed in the power basis or falling factorial basis itself. Integrals involving falling factorials are connected to the B(a, b) = \int_0^1 t^{a-1} (1-t)^{b-1} \, dt = \Gamma(a) \Gamma(b) / \Gamma(a+b) for \Re(a) > 0, \Re(b) > 0. For positive b = n, B(x+1, n) = (n-1)! / (x+1)^{(n)}, linking the reciprocal of the rising factorial to this representation. Given the relation (x)_n = (-1)^n (-x)^{(n)}, similar forms apply to falling factorials by , providing a tool for evaluating definite integrals such as those over [0,1] with powers adjusted to match the product structure. These expressions extend naturally to real arguments via the , where falling and rising factorials are defined as (x)_n = \Gamma(x+1)/\Gamma(x-n+1) and x^{(n)} = \Gamma(x+n)/\Gamma(x).

Finite Differences

The forward difference operator, denoted \Delta, is defined for a f as \Delta f(x) = f(x+1) - f(x). Higher-order forward differences are obtained by repeated application, \Delta^n f(x) = \Delta (\Delta^{n-1} f(x)). The falling factorial (x)_n = x(x-1)\cdots(x-n+1) serves as an of this operator, satisfying \Delta (x)_n = n (x)_{n-1}. This property mirrors the rule for powers in continuous and facilitates the representation of polynomials in the Newton forward difference interpolation formula. Similarly, the backward difference operator, denoted \nabla, is defined as \nabla f(x) = f(x) - f(x-1), with higher orders \nabla^n f(x) = \nabla (\nabla^{n-1} f(x)). The rising factorial x^{(n)} = x(x+1)\cdots(x+n-1) is an of \nabla, obeying \nabla x^{(n)} = n x^{(n-1)}. This relation parallels the forward case but operates in the opposite direction, aiding in backward difference expansions and analogs of . In 's divided difference , the falling factorial basis provides a natural framework for constructing interpolating polynomials, especially on nonuniform grids. For points x_1 < x_2 < \cdots < x_n, the k-th degree interpolant can be expressed using a falling factorial basis \{h_k^j(x)\}, where h_k^j(x) = \frac{1}{k!} \prod_{\ell = j-k}^{j-1} (x - x_\ell) for appropriate j > k, leading to efficient computation via scaled by grid spacings. This generalizes the classical Newton form p(x) = \sum_{j=1}^{m} f[x_1, \dots, x_j] \prod_{i=1}^{j-1} (x - x_i), with the basis enabling constant-time evaluation in spline contexts.

Advanced Connections

Stirling Numbers and Connection Coefficients

Stirling numbers of the first and second kinds serve as connection coefficients that express powers of a in terms of falling factorials and vice versa. The signed Stirling numbers of the first kind s(n,k) are defined such that the falling factorial expands as (x)_n = \sum_{k=0}^n s(n,k) \, x^k, where the sum runs over k from 0 to n, and s(n,k) = 0 for k > n or k < 0. This relation provides an explicit basis change from the \{x^k\} to the falling factorial basis \{(x)_k\}. Conversely, the of the second kind S(n,k), which count the number of ways to partition a set of n elements into k non-empty unlabeled subsets, satisfy x^n = \sum_{k=0}^n S(n,k) \, (x)_k. These coefficients S(n,k) thus convert falling factorials back to powers. The unsigned Stirling numbers of the first kind, denoted |s(n,k)| or sometimes c(n,k), arise naturally in the combinatorial interpretation of the signed versions and count the number of permutations of n elements into exactly k disjoint cycles, including fixed points as 1-cycles. This unsigned variant connects to the rising factorial through the expansion x^{(n)} = \sum_{k=0}^n |s(n,k)| \, x^k, providing a parallel basis change for the rising factorial basis \{x^{(k)}\}. The sign difference between the falling and rising cases reflects the alternating nature of the products in their definitions. To relate falling and rising factorials directly via Stirling numbers, one identity expresses the rising factorial in terms of powers using signed coefficients, followed by expansion into falling factorials: x^{(n)} = \sum_{k=0}^n s(n,k) (-1)^{n-k} x^k = \sum_{k=0}^n s(n,k) (-1)^{n-k} \sum_{j=0}^k S(k,j) (x)_j. This double sum yields the connection coefficients as products of the two Stirling types, though explicit forms often involve Lah numbers for simplification. The generating functions for these Stirling numbers are tied to the factorials themselves. For the signed Stirling numbers of the first kind, the ordinary generating function for fixed n is precisely the falling factorial: \sum_{k=0}^n s(n,k) t^k = (t)_n. Similarly, for the unsigned versions, it is the rising factorial: \sum_{k=0}^n |s(n,k)| t^k = t^{(n)}. These relations highlight the factorials as fundamental generating objects for the coefficients.

Umbral Calculus

Umbral calculus provides a symbolic framework for manipulating polynomials by treating sequences like the falling and rising factorials as analogs to ordinary powers, enabling the transfer of familiar identities from exponential generating functions to finite difference contexts. Developed rigorously in the modern era, this approach abstracts linear operators on polynomial spaces, where the falling factorial (x)_n behaves umbrally as x^n. Central to this calculus is the umbral notation, which identifies the falling factorial (x)_n with x^n under the action of associated umbral operators, such as the delta operator \phi satisfying \phi_n(x) = (x)_n. The E plays a foundational role, defined by E f(x) = f(x+1) for any f, facilitating translations in the argument that mirror in the umbral setting. The forward operator \Delta, given by \Delta = E - 1, serves as the umbral derivative, since it satisfies \Delta (x)_n = n (x)_{n-1}, paralleling the rule D x^n = n x^{n-1} for the ordinary D. This operator equivalence allows umbral calculus to recast equations in terms of more intuitive power-like manipulations. A key example is the umbral binomial theorem, which posits (x + y)^n = \sum_{k=0}^n \binom{n}{k} x^k y^{n-k} in umbral notation, where the powers denote falling factorials. Explicitly, this translates to the identity (x + y)_n = \sum_{k=0}^n \binom{n}{k} (x)_k (y)_{n-k}, known as for falling factorials, highlighting how umbral symbolism unifies binomial expansions across bases. Similarly, for rising factorials, the umbral framework adapts the notation to yield analogous addition formulas. Umbral calculus also connects to Bernoulli numbers through summation formulas involving factorials. In the classical umbral treatment, Bernoulli numbers B_n are handled via the \sum_{n=0}^\infty B_n \frac{t^n}{n!} = \frac{t}{e^t - 1}, with the umbral symbol B satisfying (B + 1)^n - B^n = \delta_{n,1}, which derives identities like \sum_{k=0}^{n-1} \binom{n}{k} B_k = \delta_{n,1}. This extends to for sums of powers, expressible umbrally as \sum_{k=1}^m k^p = \frac{(B + m)^{p+1} - B^{p+1}}{p+1}, where the power basis relates to falling factorials via change-of-basis operators, enabling efficient computation of discrete sums.

Extensions and Variations

Alternative Notations

The falling and rising factorials have roots in 18th-century , predating modern symbols. These concepts gained prominence in the through works on and , leading to diverse notations across mathematical literature. The Pochhammer symbol (x)_n, introduced by Leo August Pochhammer around 1870 in studies of hypergeometric functions, standardly denotes the rising factorial x(x+1)\cdots(x+n-1). However, variants exist: in combinatorial contexts, the same symbol (x)_n often represents the falling factorial x(x-1)\cdots(x-n+1), creating ambiguity that authors resolve by explicit definition. Other early notations include angled brackets \langle x \rangle^n for the rising factorial, as seen in some 20th-century texts on finite differences. To address notational confusion, and collaborators proposed arrow-based symbols in their 1989 work Concrete Mathematics: x^{\underline{n}} for the falling factorial and x^{\overline{n}} for the rising factorial, emphasizing the downward or upward progression in the product. These underbrace and overbrace styles, reminiscent of Knuth's up-arrow for but adapted for factorials, have influenced subsequent literature in and . Modern standardization appears in the NIST Digital Library of Mathematical Functions, which adopts x^{\underline{n}} for the falling factorial and x^{\overline{n}} for the rising factorial across combinatorial analysis, aligning with Knuth's conventions for clarity in and discrete math. This choice avoids overlap with the Pochhammer symbol, reserved there for rising factorials in contexts.

Generalizations

The q-analog of the falling factorial, known as the or q-shifted factorial, generalizes the classical product by incorporating a parameter q, typically with |q| < 1. It is defined as (a; q)_n = \prod_{k=0}^{n-1} (1 - a q^k) for positive integer n, with (a; q)0 = 1, and extends to infinite products (a; q)\infty = \lim_{n \to \infty} (a; q)_n when convergent. This deformation preserves many properties of the ordinary while introducing q-dependent structures useful in quantum groups and deformed algebras. Multivariable extensions of falling and rising factorials arise in theory and multivariate hypergeometric series, often expressed as products over multi-indices or partitions \lambda = (\lambda_1, \dots, \lambda_m). A common form is the generalized Pochhammer symbol (a)_\lambda = \prod_{i=1}^m (a - i + 1)_{\lambda_i}, where ( \cdot ){\lambda_i} denotes the univariate rising factorial; variants shift the argument by parameters like \alpha or \beta for applications in zonal polynomials and Jack polynomials. These constructions yield Vandermonde-like determinants, such as \det[(x_j - x_i){\lambda}] for multi-indices \lambda, facilitating evaluations in multivariate orthogonal polynomials and theory. Iterated generalizations include the and , which build higher-order products from the classical . The of n is the product of the first n , \text{sf}(n) = \prod_{k=1}^n k!, while the is \text{hf}(n) = \prod_{k=1}^n k^k. These functions extend growth to cumulative or powered structures, with asymptotic behaviors analyzed via for large n. Such generalizations find applications in , where q-Pochhammer symbols generate functions via infinite products like the (q; q)\infty = \sum{k=-\infty}^\infty (-1)^k q^{k(3k-1)/2}, linking distinct and odd through the . In , they form the core of _{r}\phi_s series, enabling solutions to q-difference equations and representations of quantum invariants. Multivariable versions support integrals like the Selberg integral in multiple dimensions, quantifying volumes in positive definite matrix ensembles. The classical underpin these via extensions, where (x)_n = \Gamma(x+1)/\Gamma(x-n+1) for real x.

References

  1. [1]
    Falling Factorial -- from Wolfram MathWorld
    The falling factorial is related to the rising factorial x^((n)) (aka Pochhammer symbol) by (x)_n=(-1)^n(-x)^((n)),
  2. [2]
    Rising Factorial -- from Wolfram MathWorld
    The rising factorial arises in series expansions of hypergeometric functions and generalized hypergeometric functions.
  3. [3]
    Pochhammer Symbol -- from Wolfram MathWorld
    is an unfortunate notation used in the theory of special functions for the rising factorial, also known as the rising factorial power (Graham et al. 1994, p. 48) ...
  4. [4]
    [PDF] The Falling Factorial Basis and Its Statistical Applications
    The advantage of the falling factorial basis is that it enables rapid, linear-time computations in ba- sis matrix multiplication and basis matrix inver- sion.Missing: rising | Show results with:rising
  5. [5]
    [PDF] Divided Differences, Falling Factorials, and Discrete Splines
    ... definition of the falling factorial basis ... It is not exactly equivalent, as the standard definition (190) uses a truncated rising factorial polynomial, whereas ...
  6. [6]
    [PDF] Discrete Mathematics Homework 2 Solutions
    Oct 10, 2014 · We can also express a falling factorial as the quotient of two factorials, which should look familiar. nk = n! (n − k)!. = k! (n k. ).
  7. [7]
  8. [8]
    [PDF] MATH 465 Notes
    Jan 9, 2020 · Falling factorial (n)k. Proof. First, permute the entire n-element set, then remove the last n−k elements. There is one way to remove them ...
  9. [9]
    [PDF] notes for math 184
    The falling factorials have predictable and reasonably simple summation formulas, unlike the usual power polynomials. How can we use this? The point is that ...<|control11|><|separator|>
  10. [10]
    DLMF: §5.2 Definitions ‣ Properties ‣ Chapter 5 Gamma Function
    When R ⁡ z ≤ 0 , Γ ⁡ ( z ) is defined by analytic continuation. It is a meromorphic function with no zeros, and with simple poles of residue.
  11. [11]
    None
    Nothing is retrieved...<|separator|>
  12. [12]
    [PDF] Chapter 3.3, 4.1, 4.3. Binomial Coefficient Identities - UCSD Math
    For any integer k > 0, define the falling factorial. (α)k = α(α − 1)(α − 2)···(α − k + 1) and the binomial coefficient. (α k. ) = (α)k k! = α(α − 1)(α − 2 ...
  13. [13]
    Binomial Series -- from Wolfram MathWorld
    There are several related series that are known as the binomial series. The most general is (x+a)^nu=sum_(k=0)^infty(nu; k)x^ka^(nu-k).
  14. [14]
    Random Permutations (Part 8) - UCR Math Department
    Dec 8, 2019 · The power kn counts the number of functions from n to k, where now I'm identifying a natural number with a set having that number of elements.
  15. [15]
    [PDF] Example: What is the probability of a flush in poker? (5-card, no ...
    We call ( n k) a binomial coefficient because it turns up in the Binomial Theorem. Properties: (1) ( n k). = n! k!(n − k)!= ( n n − k) have already seen ...
  16. [16]
    falling factorial - PlanetMath.org
    Mar 22, 2013 · The rising factorial is often written as (x)n ( x ) n , and referred to as the Pochhammer symbol Dlmf Mathworld (see hypergeometric series).Missing: Heinrich | Show results with:Heinrich
  17. [17]
    [PDF] Falling Factorials, Generating Functions, and Conjoint Ranking Tables
    Falling factorial powers satisfy. ∆xn = nxn−1 ,. 4. Page 5. where ∆ is the forward difference operator. A little more generally, using the two-variable.
  18. [18]
    [PDF] Discrete fractional calculus with the nabla operator - eCommons
    Properties of discrete fractional calculus in the sense of a backward difference ... [19] to denote the rising factorial function. Let α be any real number ...
  19. [19]
    [PDF] Divided Differences, Falling Factorials, and Discrete Splines - arXiv
    Mar 9, 2020 · This paper is centered around a collection of functions called the falling factorial basis, which provides an important.
  20. [20]
    Stirling Number of the First Kind -- from Wolfram MathWorld
    (n-x-1; n),. (11). where (x)_n is a falling factorial and x^((n)) is the rising factorial,. sum_(k=m)^infty(s(k,m)). (12). for x<1 (Abramowitz and Stegun 1972, ...
  21. [21]
    Probabilistic proofs of relations with Stirling numbers of the first kind ...
    The polynomial with Stirling numbers of the first kind as coefficients is equal to the falling factorial and the one with the absolute numbers to the rising ...
  22. [22]
    [PDF] A Selected Survey of Umbral Calculus
    Apr 28, 1995 · We survey the mathematical literature on umbral calculus (otherwise known as the calculus of finite differences) from its roots in the 19th ...Missing: falling | Show results with:falling
  23. [23]
    [PDF] Operational Umbral Calculus - arXiv
    Sep 1, 2024 · It can be verified that φn(x)=(x)n, the falling factorials. Later, we shall develop tools to derive expressions for basic sets, eliminating ...
  24. [24]
    Two Notes on Notation - jstor
    have become accustomed to the notation (Z)n for rising factorial powers, while many other people (e.g., statisticians) use the same notation for falling powers.<|separator|>