Consider the following Markov chain, for ; ; p; q 2 (0; 1). Find all the recurrent and transient classes. Given that we start in state 2, what is the probability that we will reach state 0 before ...
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 = ...
Abstract: Random variable with fuzzy probability and its expected value are defined. For a kind of multi-criteria decision-making problem, in which the criteria weights are precisely known and the ...
CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...
For a random walk with negative drift we study the exceedance probability (ruin probability) of a high threshold. The steps of this walk (claim sizes) constitute a stationary ergodic stable process.
Right now, I am using Probability and Random Processes for EE by Alberto Leon-Garcia. This has to be the most useless text book I have seen. The HW problems are nothing like the examples. Plus the ...
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 ...
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