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

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demo of Poisson regression, where the goal is to predict a count of things arriving, such as the number of telephone calls ...

The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...

A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...

The temporal distribution models of earthquakes represent an important theoretical basis for earthquake prediction and seismic hazard analysis. Currently, it is widely assumed in probabilistic seismic ...

Deep generative models are a popular data generation strategy used to generate high-quality samples in pictures, text, and audio and improve semi-supervised learning, domain generalization, and ...

Rock mass failure is gradually becoming more common as the number of geotechnical engineering projects continues to increase. In this paper, the probability density distributions of initial and peak ...