Prabhakar function

Last updated

Prabhakar function is a certain special function in mathematics introduced by the Indian mathematician Tilak Raj Prabhakar in a paper published in 1971. [1] The function is a three-parameter generalization of the well known two-parameter Mittag-Leffler function in mathematics. The function was originally introduced to solve certain classes of integral equations. Later the function was found to have applications in the theory of fractional calculus and also in certain areas of physics. [2]

Contents

Definition

The one-parameter and two-parameter Mittag-Leffler functions are defined first. Then the definition of the three-parameter Mittag-Leffler function, the Prabhakar function, is presented. In the following definitions, is the well known gamma function defined by

.

In the following it will be assumed that , and are all complex numbers.

One-parameter Mittag-Leffler function

The one-parameter Mittag-Leffler function is defined as [3]

Two-parameter Mittag-Leffler function

The two-parameter Mittag-Leffler function is defined as [4]

Three-parameter Mittag-Leffler function (Prabhakar function)

The three-parameter Mittag-Leffler function (Prabhakar function) is defined by [1] [5] [6]

where .

Elementary special cases

The following special cases immediately follow from the definition. [2]

  1. , the two-parameter Mittag-Leffler function.
  2. , the one-parameter Mittag-Leffler function.
  3. , the classical exponential function.

Properties

Reduction formula

The following formula can be reduced to lower the value of the third parameter . [2]

Relation with Fox–Wright function

The Prabhakar function is related to the Fox–Wright function by the following relation:

Derivatives

The derivative of the Prabhakar function is given by

There is a general expression for higher order derivatives. Let be a positive integer. The -th derivative of the Prabhakar function is given by

The following result is useful in applications.

Integrals

The following result involving Prabhakar function is known.

Laplace transforms

The following result involving Laplace transforms plays an important role in both physical applications and numerical computations of the Prabhakar function.

Prabhakar fractional calculus

The following function is known as the Prabhakar kernel in the literature. [2]

Given any function , the convolution of the Prabhakar kernel and is called the Prabhakar fractional integral:

Properties of the Prabhakar fractional integral have been extensively studied in the literature. [7] [8]

Related Research Articles

<span class="mw-page-title-main">Gamma distribution</span> Probability distribution

In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. There are two equivalent parameterizations in common use:

  1. With a shape parameter and a scale parameter .
  2. With a shape parameter and an inverse scale parameter , called a rate parameter.

Fractional calculus is a branch of mathematical analysis that studies the several different possibilities of defining real number powers or complex number powers of the differentiation operator

<span class="mw-page-title-main">Lambda cube</span>

In mathematical logic and type theory, the λ-cube is a framework introduced by Henk Barendregt to investigate the different dimensions in which the calculus of constructions is a generalization of the simply typed λ-calculus. Each dimension of the cube corresponds to a new kind of dependency between terms and types. Here, "dependency" refers to the capacity of a term or type to bind a term or type. The respective dimensions of the λ-cube correspond to:

<span class="mw-page-title-main">Mittag-Leffler function</span> Mathematical function

In mathematics, the Mittag-Leffler function is a special function, a complex function which depends on two complex parameters and . It may be defined by the following series when the real part of is strictly positive:

<span class="mw-page-title-main">Inverse-gamma distribution</span> Two-parameter family of continuous probability distributions

In probability theory and statistics, the inverse gamma distribution is a two-parameter family of continuous probability distributions on the positive real line, which is the distribution of the reciprocal of a variable distributed according to the gamma distribution.

The Havriliak–Negami relaxation is an empirical modification of the Debye relaxation model in electromagnetism. Unlike the Debye model, the Havriliak–Negami relaxation accounts for the asymmetry and broadness of the dielectric dispersion curve. The model was first used to describe the dielectric relaxation of some polymers, by adding two exponential parameters to the Debye equation:

<span class="mw-page-title-main">Kumaraswamy distribution</span>

In probability and statistics, the Kumaraswamy's double bounded distribution is a family of continuous probability distributions defined on the interval (0,1). It is similar to the beta distribution, but much simpler to use especially in simulation studies since its probability density function, cumulative distribution function and quantile functions can be expressed in closed form. This distribution was originally proposed by Poondi Kumaraswamy for variables that are lower and upper bounded with a zero-inflation. This was extended to inflations at both extremes [0,1] in later work with S. G. Fletcher.

In mathematics, Riemann's differential equation, named after Bernhard Riemann, is a generalization of the hypergeometric differential equation, allowing the regular singular points to occur anywhere on the Riemann sphere, rather than merely at 0, 1, and . The equation is also known as the Papperitz equation.

<span class="mw-page-title-main">Beta prime distribution</span> Probability distribution

In probability theory and statistics, the beta prime distribution is an absolutely continuous probability distribution. If has a beta distribution, then the odds has a beta prime distribution.

A ratio distribution is a probability distribution constructed as the distribution of the ratio of random variables having two other known distributions. Given two random variables X and Y, the distribution of the random variable Z that is formed as the ratio Z = X/Y is a ratio distribution.

The term generalized logistic distribution is used as the name for several different families of probability distributions. For example, Johnson et al. list four forms, which are listed below.

<span class="mw-page-title-main">Fox H-function</span> Generalization of the Meijer G-function and the Fox–Wright function

In mathematics, the Fox H-functionH(x) is a generalization of the Meijer G-function and the Fox–Wright function introduced by Charles Fox (1961). It is defined by a Mellin–Barnes integral

<span class="mw-page-title-main">Calculus of moving surfaces</span> Extension of the classical tensor calculus

The calculus of moving surfaces (CMS) is an extension of the classical tensor calculus to deforming manifolds. Central to the CMS is the Tensorial Time Derivative whose original definition was put forth by Jacques Hadamard. It plays the role analogous to that of the covariant derivative on differential manifolds in that it produces a tensor when applied to a tensor.

In mathematics, the Fox–Wright function (also known as Fox–Wright Psi function, not to be confused with Wright Omega function) is a generalisation of the generalised hypergeometric function pFq(z) based on ideas of Charles Fox (1928) and E. Maitland Wright (1935):

In applied mathematics and mathematical analysis, the fractal derivative or Hausdorff derivative is a non-Newtonian generalization of the derivative dealing with the measurement of fractals, defined in fractal geometry. Fractal derivatives were created for the study of anomalous diffusion, by which traditional approaches fail to factor in the fractal nature of the media. A fractal measure t is scaled according to tα. Such a derivative is local, in contrast to the similarly applied fractional derivative. Fractal calculus is formulated as a generalization of standard calculus.

In the fields of dynamical systems and control theory, a fractional-order system is a dynamical system that can be modeled by a fractional differential equation containing derivatives of non-integer order. Such systems are said to have fractional dynamics. Derivatives and integrals of fractional orders are used to describe objects that can be characterized by power-law nonlocality, power-law long-range dependence or fractal properties. Fractional-order systems are useful in studying the anomalous behavior of dynamical systems in physics, electrochemistry, biology, viscoelasticity and chaotic systems.

The Mittag-Leffler distributions are two families of probability distributions on the half-line . They are parametrized by a real or . Both are defined with the Mittag-Leffler function, named after Gösta Mittag-Leffler.

In mathematics, Katugampola fractional operators are integral operators that generalize the Riemann–Liouville and the Hadamard fractional operators into a unique form. The Katugampola fractional integral generalizes both the Riemann–Liouville fractional integral and the Hadamard fractional integral into a single form and It is also closely related to the Erdelyi–Kober operator that generalizes the Riemann–Liouville fractional integral. Katugampola fractional derivative has been defined using the Katugampola fractional integral and as with any other fractional differential operator, it also extends the possibility of taking real number powers or complex number powers of the integral and differential operators.

<span class="mw-page-title-main">Stable count distribution</span> Probability distribution

In probability theory, the stable count distribution is the conjugate prior of a one-sided stable distribution. This distribution was discovered by Stephen Lihn in his 2017 study of daily distributions of the S&P 500 and the VIX. The stable distribution family is also sometimes referred to as the Lévy alpha-stable distribution, after Paul Lévy, the first mathematician to have studied it.

<span class="mw-page-title-main">Kaniadakis Gamma distribution</span> Continuous probability distribution

The Kaniadakis Generalized Gamma distribution is a four-parameter family of continuous statistical distributions, supported on a semi-infinite interval [0,∞), which arising from the Kaniadakis statistics. It is one example of a Kaniadakis distribution. The κ-Gamma is a deformation of the Generalized Gamma distribution.

References

  1. 1 2 Tilak Raj Prabhakar (1971). "A singular integral equation with a generalized Mittag-Leffler function in the kernel" (PDF). Yoklohama Mathematics Journal. 19 (1): 7–15. Retrieved 27 December 2023.
  2. 1 2 3 4 Andrea Giusti, Ivano Colombaro, Roberto Garra (2020). "A practical guide to Prabhakar fractional calculus". Fractional Calculus and Applied Analysis. 25 (1): 9–54. arXiv: 2002.10978 . doi:10.1515/fca-2020-0002.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  3. Rudolf Gorenflo, Anatoly A. Kilbas, Francesco Mainardi, Sergei V. Rogosin (2014). Mittag-Leffler Functions, Related Topics and Applications. Springer. p. 17. ISBN   978-3-662-43929-6.{{cite book}}: CS1 maint: multiple names: authors list (link)
  4. Rudolf Gorenflo, Anatoly A. Kilbas, Francesco Mainardi, Sergei V. Rogosin (2014). Mittag-Leffler Functions, Related Topics and Applications. Springer. p. 56. ISBN   978-3-662-43929-6.{{cite book}}: CS1 maint: multiple names: authors list (link)
  5. Rudolf Gorenflo, Anatoly A. Kilbas, Francesco Mainardi, Sergei V. Rogosin (2014). Mittag-Leffler Functions, Related Topics and Applications. Springer. p. 97. ISBN   978-3-662-43929-6.{{cite book}}: CS1 maint: multiple names: authors list (link)
  6. Roberto Garra and Roberto Garrappa (2018). "The Prabhakar or three parameter Mittag–Leffler function: theory and application". Communications in Nonlinear Science and Numerical Simulation. 56: 314–329. arXiv: 1708.07298v2 . Bibcode:2018CNSNS..56..314G. doi:10.1016/j.cnsns.2017.08.018.
  7. Anatoly A. Kilbas, Megumi Saigo and R. K. Saxena (2004). "Generalized mittag-leffler function and generalized fractional calculus operators". Integral Transforms and Special Functions. 15 (1): 31–49. doi:10.1080/10652460310001600717. S2CID   120569191.
  8. F. Polito and Z. Tomovski (2016). "Some properties of Prabhakar-type fractional calculus operators". Fractional Differential Calculus. 6 (1): 73–94. arXiv: 1508.03224 . doi:10.7153/fdc-06-05.