Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn to assess risk and potential gains.

Abstract: Aiming at suppressing the switching frequency harmonics in the integrated permanent magnet synchronous motor (PMSM) systems, a discrete random switching period (DRSP) space vector pulse ...

(1) PROF. FRECHET'S "Généralités" represents the first volume only of a treatise which, as a whole, is to form part of the very important "Traité du calcul des probabilités"edited by Prof. Borel. The ...

The total area under the curve must equal 1, representing the fact that the probability of some outcome occurring within the entire range is certain. \[\int_{-\infty}^{\infty}f\left(x\right)dx=1\] ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

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, ...

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, ...

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 ...

ABSTRACT: In this paper, a collection of statistical correlation methods is used in the study of aquifer potentials in Abia State of south-eastern Nigeria. The Physiology, geomorphology and ...

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 ...