Upon starting the program, the user is allowed to select which distribution they would like to generate random variables for, as well as specify the number of variables (N) and distribution parameters ...

Continuous random variables Continuous random variables A continuous random variable is a type of variable that can take on any value within a given range. Unlike discrete random variables, which have ...

A discrete random variable is a type of random variable that can take on a countable set of distinct values. Common examples include the number of children in a family, the outcome of rolling a die, ...

Definition and Marginal Distributions Discrete A discrete bivariate distribution represents the joint probability distribution of a pair of random variables. For discrete random variables with a ...

The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm. A ...

Part-I, Probability (Chapters 1 – 3), lays a solid groundwork for probability theory, and introduces applications in counting, gambling, reliability, and security. Part-II, Random Variables (Chapters ...

Traditionally, the uncertainty qualification is utilized with the known probability distribution function (PDF). However, in some scenarios, the PDFs of some uncertain variables are modeled ...

2 RELIABILITY MODEL CONSIDERING PROBABILISTIC AND INTERVAL VARIABLES 2.1 Probability-based reliability model In the traditional probability-based reliability analysis method, the uncertainties are ...