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Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.
2
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2
answers
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An "obvious" probability lemma about random words
Fix some positive integers $p,n,k$. Let $w$ be chosen uniformly at random from $[k]^n$ (the set of $n$ length words/sequences where each entry is in $\{1,\ldots,k\}$). Let $A_i$ be the event that $w_ …
5
votes
4
answers
384
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Concentration of closed random walks
Consider a random walk $S_n=\sum_{i=1}^n X_i$ where $P(X_i=+1)=P(X_i=-1)=1/2$ with $n$ large. By Chernoff's bound we know that, for example, $\sum_{i=1}^{n/2} X_i=O(\sqrt{n})$ with high probability.
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2
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Accepted
Concentration of closed random walks
I believe the following coupling argument shows that (in particular) if we specify that the random walk ends at 0 then halfway through the walk the probability that we're within distance $\lambda$ of …
12
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3
answers
1k
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A Modern Proof of Erdos and Renyi's 1959 Random Graph Paper?
In their paper, Erdos and Renyi consider a random graph with a fixed number of edges, as opposed to the more modern approach of adding each edge independently with probability $p$. From what I unders …
5
votes
Accepted
A Modern Proof of Erdos and Renyi's 1959 Random Graph Paper?
The most satisfying solution I've seen so far are these notes by Sabastian Roch (see section 2.2.3, and in particular claim 2.25). He first argues that the only components besides the giant one are i …