Particle emission concept and probabilistic consideration of the development of infections in systems

Exploring advanced statistical methods, this book presents a probabilistic prognosis model that utilizes the mean n-day logarithm of historical case numbers to establish a probability density exponent. It also introduces the particle emission concept, which is based on contact and distribution rates. This concept enhances the exponent of probable outcomes, allowing for the formation of groups based on predictive analytics. The book combines mathematical theory with practical applications in forecasting, making it a valuable resource for understanding complex data trends.