A GUI-based tool for analyzing random variables and stochastic processes. The project provides both statistical measures and visualization tools for probability and stochastic process analysis.

Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...

Abstract: In this chapter, we introduce the concept of a random variable and develop the procedures for characterizing random variables, including the cumulative distribution function, as well as the ...

Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...

Theoretical simulation of random processes means carrying out numerical experiments using artificial random variables. The aim of simulation is not to reproduce the behavior of a physical system, but ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...

Abstract: Offers a complete survey of random signal analysis, including probability and random variable fundamentals, random processes, signal analysis, and optimal filter theory -each essential to ...

Journal of Applied Probability and Advances in Applied Probability have for four decades provided a forum for original research and reviews in applied probability, mapping the development of ...

We give necessary and sufficient conditions for $P(\sum{_{n=1}^{\infty}}(A + S_{n})^{-1} < \infty) = 1$ in terms of E(∑n=1 ∞(A + Sn)-1), where Sn is the sum of n ...

Stop-loss and limited loss random variables are two important transforms of a loss random variable and appear in many modeling problems in insurance, finance, and other fields. Risk levels of a loss ...