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 ...

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 ...

We study the tail behavior of regularly varying infinitely divisible random vectors and additive processes, i.e. stochastic processes with independent but not necessarily stationary increments. We ...

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 ...

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 ...

We give necessary and sufficient conditions for $P(\sum{_{n=1}^{\infty}}(A + S_{n})^{-1} < \infty) = 1$ in terms of E(∑n=1 ∞(A + Sn)-1), where Sn is the sum of n ...

This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option to ...

This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option to ...