Probability functions depending upon parameters are represented as integrals over sets given by inequalities. New derivative formulas for the intergrals over a volume are considered. Derivatives are presented as sums of integrals over a volume and over a surface. Two examples are discussed: probability functions with linear constraints (random right-hand sides), and a dynamical shut-down proble...

Probability density functions (pdfs) are employed to evaluate the distribution of velocities in the global ocean. This study computes pdfs of ocean surface velocity using altimetric data from the TOPEX/Poseidon satellite. Results show that the shape of the observed pdfs changes with the size of the domain over which they are calculated: if data are drawn from a small region of the ocean, the pd...

Random quanti t ies of interest in operations research models can often be determined conveniently in the form of transforms. Hence, numerical t ransform inversion can be an effective way to obtain desired numerical values of cumulative distribution functions, probability density functions and probability mass functions. However, numerical transform inversion has not been widely used. This lack...

Context. Two-point correlation functions are used throughout cosmology as a measure for the statistics of random fields. When used in Bayesian parameter estimation, their likelihood function is usually replaced by a Gaussian approximation. However, this has been shown to be insufficient. Aims. For the case of Gaussian random fields, we search for an exact probability distribution of correlation...

As a part of our works on effective properties of probability distributions, we deal with the corresponding characteristic functions. A sequence of probability distributions is computable if and only if the corresponding sequence of characteristic functions is computable. As for the onvergence problem, the effectivized Glivenko’s theorem holds. Effectivizations of Bochner’s theorem and de Moivr...

A new approach is used to determine the transient probability functions of Markov processes. This new solution method is a sample path counting approach and uses dual processes and randomization. The approach is illustrated by determining transient probability functions for a three-state Markov process. This approach also provides a way to calculate transient probability functions for Markov pr...

This paper examines two approaches to estimating implied risk-neutral probability density functions from the prices of European-style options. It sets up a monte carlo test to evaluate alternative techniques’ ability to recover simulated distributions based on Heston’s (1993) stochastic volatility model. The paper tests both for the accuracy and stability of the estimated summary statistics fro...