CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...
Let (Xn)n1=1, be a sequence of i.i.d. random variables distributed uniformly in [ 1; 1]. Show that the following sequences (Yn)n1=1 converge in probability to some limit. n (a) Yn = Qi=1 Xi. (b) Yn = ...
CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...
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 ...
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 ...
This course is available on the MSc in Financial Mathematics, MSc in Mathematics and Computation and MSc in Quantitative Methods for Risk Management. This course is available with permission as an ...
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