Gaussian processes offer a versatile framework to model and analyse continuous random phenomena, making them particularly useful in quantifying the probability of ruin in financial and insurance ...
Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...
Probability is all about how likely is an event to happen. For a random experiment with sample space S, the probability of happening of an event A is calculated by the probability formula n (A)/n (S).
Probability and statistics, the branches of mathematics concerned with the laws governing random events, including the collection, analysis, interpretation, and display of numerical data. Learn more about the history of probability and statistics in this article.
CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...
CATALOG DESCRIPTION: Advanced topics in random processes: point processes, Wiener processes; Markov processes, spectral representation, series expansion of random processes, linear filtering, Wiener ...
Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...
Random walks constitute one of the most fundamental models in the study of stochastic processes, representing systems that evolve in a sequence of random steps. Their applications range from modelling ...
Ivan Bajic (ibajic at ensc.sfu.ca) Office hours: Monday and Wednesday, 13:00-14:00 online (Zoom, see the link in course materials) Introduction to the theories of probability and random variables, and ...
JSTOR Daily: Random Rewards, Fractional Brownian Local Times and Stable Self-Similar Processes