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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.
3
votes
The power of two random choices with pairwise independence
Let me sketch why I think the answer is still $\Theta(\sqrt{n})$.
Given any distribution such that, for each pair of the $2n$ random numbers, the probability that they are the same is $1/n$, we can s …
1
vote
Can averaging order statistics produce independent Gaussian random variables?
When you average a chain of ascending numbers, for two of the averages to be close to each other, three of the original numbers must be close to each other. This means that the probability of two of t …
7
votes
Is every submartingale a convex function of a martingale?
Not every. Every convex function is either bounded below or monotonic. The first kind cannot produce any submartingale that is not bounded below. The second kind cannot produce any submartingale that, …
5
votes
Accepted
Which type of convergence for this sequence of random variables?
Yes in probability: The definitions of convergence in distribution to a constant random variable and convergence in probability to a constant random variable are the same.
No almost surely: If we let …
8
votes
Accepted
Expected value of the minimum with limited independence
Let $u_k$ be the number of variables with value exactly $k$. If you pick a distribution of the $u_k$ such that $E[u_k]=1$, $E[u_k^2] = 2-1/n$, $E[u_ku_l] = 1-1/n$ for $k \neq l$ and $\sum_{k=1}^n u_k$ …
9
votes
Accepted
Smallest $k$ so that $k$-wise independence guarantees a constant expected minimum
I can do $k\geq 4$. This is done using a method similar to the upper bound from last time. Let $N_m$ be the number of samples that are at most $m$. Then we wish to upper bound the probability that $N_ …
4
votes
Probabilistic method used to prove existence theorems
The best deterministic constructions of matrices with the restricted isometry property are much worse than random matrices. Matrices with the restricted isometry property are important in compressed s …
11
votes
Probability that biggest area stays greater than 1/2 in a unit square cut by random lines
Aaron and fedja have pointed out that the problem is equivalent to finding the convex region in the plane with area $1/2$ with the highest probability that a random line does not intersect it.
The o …
16
votes
Accepted
Is the circle in the square best at avoiding random lines?
Calculus of variation shows that the segment of the boundary of the optimal shape where the tangent line intersects two opposite sides must be a parabola.
To see, this observe that the tangent line …
4
votes
Convergence to a k-dimensional Gaussian vector
This has nothing to do with convergence, as there are counterexamples which do not depend on $N$. It also has nothing to do with time, as you didn't specify any condition that would restrict how the s …
2
votes
Geometry interpretation of any continuous random variable
Let $f_X$ be the pdf of $X$. Let $$C = \int_{-\infty}^{\infty} f_X(x) \log F_X(x) dx $$
and define $$\mathscr{Z}_n = \left\{ x_1,\dots, x_n \in \textrm{Supp}(X) \mid \sum_{i=1}^n \log f_X(x_i) \geq n …
2
votes
Exponential (or other) families of distributions on manifolds.
I claim that the answer is yes. The key point that makes a distribution exponential is that there is a set of sufficient statistics, of the dimension of the manifold, that are additive.
On an $n$-dim …
11
votes
Accepted
A trick or a general technique? (Probabilistic Method)
One way to see this technique is as a way of dealing with certain bad cases. $E[P/Q]$ can be unhelpfully dragged up by the inclusion of certain cases where $Q$ is small and $P$ is medium. $E[P]/E[Q]$ …
2
votes
Accepted
Conditional expectation and algebraic expressions
Clearly not. Let the measure space be the uniform measure on {$1,2,3,4$}. $A$ allows you to discern whether the number is greater or less than $2.5$ or not. $B$ allows you to discern whether the numbe …
3
votes
Accepted
Variance of projection of vectors onto random subspace
It suffices to calculate $\mathbb E ( (P_E)_{ab} (P_E)_{cd})$ for all $1\leq a,b,c,d\leq n$, or, equivalently, calculate $\mathbb E( P_E \otimes P_E ) \in \mathbb R^n \otimes \mathbb R^n \otimes \math …