When fuzzy information is taken into consideration in design, it is difficult to analyze the reliability of machine parts because we usually must deal with random information and fuzzy information ...

This work provides new bounds on the difference between the entropies of two discrete random variables in terms of the local and total variation distances between their probability mass functions. The ...

This table represents a discrete probability function, which shows the probability associated with each possible value of a discrete random variable. Such distributions can also be displayed ...

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 random variable is one whose value is unknown or a function that assigns values to each of an experiment’s outcomes. A random variable can be discrete or continuous.

Joint probability is a statistical measure that calculates the likelihood of two events occurring together and at the same point in time.

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 ...

Spread the loveIn the field of statistics and probability, marginal distribution plays a critical role in understanding the behavior of variables. It is a method used to determine the probability ...

Learning the joint probability of random variables (RVs) is the cornerstone of statistical signal processing and machine learning. However, direct nonparametric estimation for high-dimensional joint ...