In mathematics, the beta function, also called the Euler integral of the first kind, is a special function that is closely related to the gamma function and to binomial coefficients. It is defined by the integral
for complex number inputs x, y such that Re x > 0, Re y > 0.
The beta function is symmetric, meaning that
for all inputs x and y.
(A proof is given below in § Relationship to the gamma function.)
Relationship to the gamma functionEdit
A simple derivation of the relation can be found in Emil Artin's book The Gamma Function, page 18–19. To derive this relation, write the product of two factorials as
Changing variables by u = zt and v = z(1 − t) produces
Dividing both sides by gives the desired result.
The stated identity may be seen as a particular case of the identity for the integral of a convolution. Taking
where ψ(x) is the digamma function.
Stirling's approximation gives the asymptotic formula
for large x and large y. If on the other hand x is large and y is fixed, then
Other identities and formulasEdit
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The integral defining the beta function may be rewritten in a variety of ways, including the following:
The beta function can be written as an infinite sum
- [dubious ]
and as an infinite product
The beta function satisfies several identities analogous to corresponding identities for binomial coefficients, including a version of Pascal's identity
and a simple recurrence on one coordinate:
Evaluations at particular points may simplify significantly; for example,
Euler's integral for the beta function may be converted into an integral over the Pochhammer contour C as
This Pochhammer contour integral converges for all values of α and β and so gives the analytic continuation of the beta function.
Moreover, for integer n, Β can be factored to give a closed form interpolation function for continuous values of k:
The beta function was the first known scattering amplitude in string theory, first conjectured by Gabriele Veneziano. It also occurs in the theory of the preferential attachment process, a type of stochastic urn process.
Incomplete beta functionEdit
The incomplete beta function, a generalization of the beta function, is defined as
For x = 1, the incomplete beta function coincides with the complete beta function. The relationship between the two functions is like that between the gamma function and its generalization the incomplete gamma function.
The regularized incomplete beta function (or regularized beta function for short) is defined in terms of the incomplete beta function and the complete beta function:
The regularized incomplete beta function is the cumulative distribution function of the beta distribution, and is related to the cumulative distribution function of a random variable X following a binomial distribution with probability of single success p and number of Bernoulli trials n:
Multivariate beta functionEdit
The beta function can be extended to a function with more than two arguments:
This multivariate beta function is used in the definition of the Dirichlet distribution. Its relationship to the beta function is analogous to the relationship between multinomial coefficients and binomial coefficients.
Even if unavailable directly, the complete and incomplete beta function values can be calculated using functions commonly included in spreadsheet or computer algebra systems. In Excel, for example, the complete beta value can be calculated from the
Value = Exp(GammaLn(a) + GammaLn(b) − GammaLn(a + b))
An incomplete beta value can be calculated as:
Value = BetaDist(x, a, b) * Exp(GammaLn(a) + GammaLn(b) − GammaLn(a + b)).
These result follow from the properties listed above.
betainc (incomplete beta function) in MATLAB and GNU Octave,
pbeta (probability of beta distribution) in R, or
special.betainc in Python's SciPy package compute the regularized incomplete beta function—which is, in fact, the cumulative beta distribution—and so, to get the actual incomplete beta function, one must multiply the result of
betainc by the result returned by the corresponding
beta function. In Mathematica,
Beta[x, a, b] and
BetaRegularized[x, a, b] give and , respectively.
- Beta distribution and Beta prime distribution, two probability distributions related to the beta function
- Jacobi sum, the analogue of the beta function over finite fields.
- Nörlund–Rice integral
- Yule–Simon distribution
This article includes a list of references, but its sources remain unclear because it has insufficient inline citations. (November 2010) (Learn how and when to remove this template message)
- Askey, R. A.; Roy, R. (2010), "Beta function", in Olver, Frank W. J.; Lozier, Daniel M.; Boisvert, Ronald F.; Clark, Charles W. (eds.), NIST Handbook of Mathematical Functions, Cambridge University Press, ISBN 978-0-521-19225-5, MR 2723248
- Zelen, M.; Severo, N. C. (1972), "26. Probability functions", in Abramowitz, Milton; Stegun, Irene A. (eds.), Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, New York: Dover Publications, pp. 925–995, ISBN 978-0-486-61272-0
- Davis, Philip J. (1972), "6. Gamma function and related functions", in Abramowitz, Milton; Stegun, Irene A. (eds.), Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, New York: Dover Publications, ISBN 978-0-486-61272-0
- Paris, R. B. (2010), "Incomplete beta functions", in Olver, Frank W. J.; Lozier, Daniel M.; Boisvert, Ronald F.; Clark, Charles W. (eds.), NIST Handbook of Mathematical Functions, Cambridge University Press, ISBN 978-0-521-19225-5, MR 2723248
- Press, W. H.; Teukolsky, SA; Vetterling, WT; Flannery, BP (2007), "Section 6.1 Gamma Function, Beta Function, Factorials", Numerical Recipes: The Art of Scientific Computing (3rd ed.), New York: Cambridge University Press, ISBN 978-0-521-88068-8
- Hazewinkel, Michiel, ed. (2001) , "Beta-function", Encyclopedia of Mathematics, Springer Science+Business Media B.V. / Kluwer Academic Publishers, ISBN 978-1-55608-010-4
- "Evaluation of beta function using Laplace transform". PlanetMath.
- Arbitrarily accurate values can be obtained from: