Gaussian q-distribution

Source: Wikipedia, the free encyclopedia.

In

uniform distribution and the normal (Gaussian) distribution. It was introduced by Diaz and Teruel.[clarification needed] It is a q-analog of the Gaussian or normal distribution
.

The distribution is symmetric about zero and is bounded, except for the limiting case of the normal distribution. The limiting uniform distribution is on the range -1 to +1.

Definition

The Gaussian q-density.

Let q be a real number in the interval [0, 1). The probability density function of the Gaussian q-distribution is given by

where

The q-analogue [t]q of the real number is given by

The q-analogue of the exponential function is the q-exponential, Ex
q
, which is given by

where the q-analogue of the

q-factorial
, [n]q!, which is in turn given by

for an integer n > 2 and [1]q! = [0]q! = 1.

The Cumulative Gaussian q-distribution.

The cumulative distribution function of the Gaussian q-distribution is given by

where the integration symbol denotes the Jackson integral.

The function Gq is given explicitly by

where

Moments

The moments of the Gaussian q-distribution are given by

where the symbol [2n − 1]!! is the q-analogue of the double factorial given by

See also

References

  • Díaz, R.; Pariguan, E. (2009). "On the Gaussian q-distribution".
    S2CID 115175228
    .
  • Diaz, R.; Teruel, C. (2005). "q,k-Generalized Gamma and Beta Functions" (PDF).
    S2CID 73643153
    .
  • van Leeuwen, H.; Maassen, H. (1995). "A q deformation of the Gauss distribution" (PDF).
    S2CID 13934946
    .
  • Exton, H. (1983), q-Hypergeometric Functions and Applications, New York: Halstead Press, Chichester: Ellis Horwood, 1983,