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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
Accepted
On a random partition
For fixed $n$ and $k \le n$ the distance $|X_k-Y_k|$ is uniformly distributed in $[0,1/(2n)]$. Thus
if $\alpha_n<1/(2n)$, then
$$P\left[\max_{1 \le k \le n}|X_k-Y_k| \le \alpha_n \right]=(1-2n\alpha …
1
vote
Probability of returning to starting point before hitting adjacent point for RW on Z^2
There is a symmetry argument based on uniform spanning trees. If you ask for the effective resistance across an edge $e$ in the discrete torus torus $G_n=[-n,n]^2$ with periodic boundary conditions, i …
3
votes
Accepted
Bounding maximum probabilities in sum of i.i.d discrete RVs
The requested estimate follows from a theorem of Kesten [2] about concentration functions.
See in particular the inequality (1.6) on page 135 of [2]. Taking $L=\lambda<1$ in
this inequality gives the …
2
votes
Series of random variables tending to infinity P.a.s. and in L^2
This question would be more suitable for MSE. Indeed the expectations tend to infinity. This follows from Fatou’s lemma.
All you need are the first and fourth assumptions. The second and third assumpt …
6
votes
Accepted
Does there exist a constant $C$, such that, $\Pr[\max_k|\sum_{i\neq k}X_i|\ge t]\le C\Pr[|\s...
Alas, no such inequality can hold. Suppose that the symmetric $X_i$ take values $\pm 1$ and $t=n-1$. Then
$$
\Pr[\max_{k \in [n]} |\sum_{i \in [n] \setminus \{k\}} X_i| \ge t] =(n+1)2^{1-n}
$$
but
$ …
15
votes
Accepted
How many people have the same exact number of hairs?
This question has been studied extensively in the computer science literature under the name "balls in bins"; see [1] which gives quite tight bounds in Theorem 1, page 161 and also describes prior wo …
2
votes
Accepted
CLT for bounded difference functions
In the general setting you propose, the answer is negative. Suppose that $X_i$ take the values $\pm 1$ with equal probability. Let $h: {\mathbb R} \to {\mathbb R}$ be a Lipschitz function with consta …
0
votes
Accepted
Probability of getting all pattern combinations in moving window over a vector of characters
The expected length needed to see all patterns of length $k$ in an alphabet of size $a$ is $k \ln(a) a^k (1+o(1))$.
See Propositions 11.9 and 11.10 in [1] for the case $a=2$.
[1] Levin, David A., and …
5
votes
How many proofs of the Polya's recurrent theorem are there?
It is amusing that a unit flow of finite energy in the $d$-dimensional lattice for $d \ge 3$ can be easily constructed from Polya's urn; see
``Polya's theorem on random walks via Polya's urn'', Amer …
10
votes
Expected value of non-negative iid random variables
The canonical argument proving the upper bound is in the comment by Mathworker21, which has now been posted as an answer. I just want to add that the constant $e$ obtained there is sharp. Indeed, if …
4
votes
Tail bound for a martingale
Alas, the general bound you are hoping for cannot hold. Take $X_0:=1$ and continue the sequence as a simple random walk with probability $1/k$ and as the all ones sequence with probability $1-1/k$. T …
2
votes
Accepted
Maximum of a sequence is $o(\sqrt{n})$
First suppose that hypotheses (a) and (b) hold. I will write $w_{i,n}$ instead of $w_i^n$ for clarity.
Given $\epsilon>0$, the Monotone convergence theorem implies that there exists $M$ such that $ …
3
votes
Accepted
How to derive this change of measure identity in multi-armed bandits?
Shishir, this is quite elementary: write the probability $P_2(\omega)$ of any individual bit sequence $\omega$ as $P_1(\omega) f(\omega)$ where by definition, $f(\omega)=\exp(-\hat{kl}_n)$. Finally, s …
3
votes
Hitting time for two out of three random walk particles
Expanding the comment above to a complete proof of Noam Elkies' formula:
Let $\tau$ be the first meeting time for independent simple random walks $X_t, Y_t$ and $Z_t$ started at the even points $x<y …
2
votes
Accepted
Relaxing conditional independent assumption
A sufficient condition to have $Y⊥D|Z$ is that $f$ is injective. The sharp condition (if $Y$ and $D$ are not specified) is
$(*)$ $\sigma(X)$ should be contained in the completion of $\sigma(Z) …