Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...

Abstract: This paper addresses the problem of designing nonlinear discrete-time dynamical systems for prospective use in low-complexity random signal generators. Drawing upon ergodic systems theory, ...

Background: Although several strategies for modelling competing events in discrete event simulation (DES) exist, a methodological gap for the event-specific probabilities and distributions (ESPD) ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

I am new to using SALib and currently, I have a model that contains continuous and discrete input variables. I read the closed issues and understood the workaround of rounding the floats to integers ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...

This Python function creates a time-series (discrete-time random process) with a specific autocorrelation function (ACF) and continuous probability distribution, e.g with predefined probability ...