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

Stein's method has emerged as a powerful and versatile tool in probability theory for deriving error bounds in distributional approximations. Originally developed to ...

Continuous probabilistic techniques involving simulation can help managers predict the likelihood of time and cost overruns in all types and sizes of oil and gas projects. By deriving time and cost ...

Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...

A key issue in complex systems design is measuring the 'goodness' of a design, i.e. finding a criterion through which a particular design is determined to be the 'best'. Traditional choices in ...

The purpose of the Institute of Mathematical Statistics (IMS) is to foster the development and dissemination of the theory and applications of statistics and probability. The Institute was formed at a ...

Researchers in China have developed an error-aware probabilistic update (EaPU) method that dramatically improves the ...

Sampling is a tool researchers use for marketing, sociology or empirical study. In order for sampling to be productive, the data analysis must not be tainted. There are techniques for creating a ...