Abstract: Complex random variables arise naturally in many settings and their properties are of general interest. Past work on complex variables has mainly focused on their second-order structure, as ...

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 ...

TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Edited by Thomas C. Südhof, Stanford University School of Medicine, Stanford, CA, and approved August 15, 2016 (received for review March 31, 2016) ...

To find the probability that a random sample of 1,000 people contains less than 48.5% female or more than 53.5% female when the population's female ratio is 51.1%, we use the binomial distribution.

What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...

Fine-scale exogenous attention within the foveola selectively enhances contrast gain at low-to-mid spatial frequencies while increasing response gain across a broad spatial frequency range.

What are each national team’s chances of winning the World Cup? We’ve built a statistical model to try to answer that question rigorously. The model works in two steps: first we measure each team’s ...

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 ...