The Class of (p,q)-spherical Distributions with an Extension of the Sector and Circle Number Functions

Abstract

For evaluating the probabilities of arbitrary random events with respect to a given multivariate probability distribution, specific techniques are of great interest. An important two-dimensional high risk limit law is the Gauss-exponential distribution whose probabilities can be dealt with based on the Gauss–Laplace law. The latter will be considered here as an element of the newly-introduced family of ( p , q ) -spherical distributions. Based on a suitably-defined non-Euclidean arc-length measure on ( p , q ) -circles, we prove geometric and stochastic representations of these distributions and correspondingly distributed random vectors, respectively. These representations allow dealing with the new probability measures similarly to with elliptically-contoured distributions and more general homogeneous star-shaped ones. This is demonstrated by the generalization of the Box–Muller simulation method. In passing, we prove an extension of the sector and circle number functions.

Keywords

• Gauss-exponential distribution
• Gauss–Laplace distribution
• stochastic vector representation
• geometric measure representation
• (p,q)-generalized polar coordinates
• (p,q)-arc length
• dynamic intersection proportion function
• (p,q)-generalized Box–Muller simulation method
• (p,q)-spherical uniform distribution
• dynamic geometric disintegration