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Five problems related to probability theory, covering topics such as convergence of random variables, weak convergence, martingales, and stochastic processes. The problems involve showing that the expected value of a random variable converges almost surely and in l1 given an increasing sequence of sigma-algebras, proving weak convergence of a sequence of random variables to a standard normal distribution, and applying the glivenko-cantelli theorem. Additionally, there are problems on finding a function making a sequence of random variables a martingale and finding the laplace transform of the hitting time of a random walk. These problems require a strong understanding of probability theory and stochastic processes.
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∑n j=1 Xn,j^ , and assume that^ E(S (^2) n) = 1 and ∑n j=1 E(|Xn,j^ | (^3) ) → 0. Prove that Sn converges weakly to a standard normal.
For n ∈ N, let Fˆn : R → [0, 1] be defined as Fˆn(t) =
∑n j=1 1 (−∞,t](Xj^ ) n.^ Prove that supt∈[0,1]
∣ Fˆn(t)^ −^ t
∣ →^ 0, a.s. (Hint: Consider first t of the form (^) Mk , k = 0,... , M , for some large M. Estimate the differences for other choices of t from these).
∑n j=1 Dj^. (a) Find a function Λ : R → R such that for each θ, (eθXn−Λ(θ)n^ : n ∈ Z+) is a martingale. (b) Suppose that p ≥ 12. Let τ = inf{n ∈ Z+ : Xn = 1}. Find the Laplace transform Ee−ρτ^ , ρ > 0.