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

Stochastic volatility is the unpredictable nature of asset price volatility over time. It's a flexible alternative to the Black Scholes' constant volatility assumption.

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, ...

The binomial distribution is a key concept in probability that models situations where you repeat the same experiment several times, and each time there are only two possible outcomes—success or ...

A courseware module that covers the fundamental concepts in probability theory and their implications in data science. Topics include probability, random variables, and Bayes' Theorem.

Forecasting for any small business involves guesswork. You know your business and its past performance, but you may not be comfortable predicting the future. Using Excel is a great way to perform what ...

1 Guangzhou Power Supply Co. Ltd., China Southern Power Grid, Guangzhou, China 2 School of Electric Power Engineering, South China University of Technology, Guangzhou, China This paper proposes an ...

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 ...

Abstract: 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 ...