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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 votes

When is a function on symmetric positive definite matrices an expectation of Gaussian?

Here's an approach to determine if $\det(C)$ is of this form with $F$ analytic and $n=2$. By Sylvester's criterion a matrix $\begin{pmatrix} a& b \\ b & c\end{pmatrix}$ is symmetric positive semidefin …
Bjørn Kjos-Hanssen's user avatar
1 vote

Probability of a given string being a substring of another string

Let $A_t$ be the event that $S_1$ is a substring of $S_2$, $S_2=pS_1q$, where the length of $p$ is $t$. Then the probability of $\cup_t A_t$ can be found by inclusion-exclusion as $$\sum P(A_t)-\sum P …
Bjørn Kjos-Hanssen's user avatar
3 votes

A definite integral related to sample variances of bivariate Gaussians

It seems that Wolfram Alpha understands this integral. Its answers are given in terms of modified Bessel functions of the first kind $I_k$. It seems that the result is, for $A(k,c):=I(n,c)$, with $n …
Bjørn Kjos-Hanssen's user avatar
3 votes
1 answer
225 views

Brownian level sets and continuous functions

Let $V_t$ and $W_t$ be independent standard Wiener processes ($t\ge 0$, $W_t,V_t\in\mathbb R$). Let $C$ be the event that there is a continuous function $f$ such that for all $s$, $t$, $$ W_t=W_s\iff …
Bjørn Kjos-Hanssen's user avatar
1 vote

Is it true that the quantile function of an $L^1$ random variable is $L^2(]0,1[)$?

Sinve you mentioned famous examples, here is a famous counterexample: power law distributions.
Bjørn Kjos-Hanssen's user avatar
3 votes

Distinguishing between urn probability models

As you point out, the colors observed will have the same distribution with each of these models. Statistical tests involve asking "what is the probability of what is observed according to various …
Bjørn Kjos-Hanssen's user avatar
4 votes
Accepted

When are events in tail $\sigma$-algebra the limsup of some sequence of events?

No, let $\mathcal S_0=\{\{0,1\},\emptyset\}$ and let $\mathcal S_1$ be the powerset of $\{0,1\}$. Let $\mathcal F_n=\mathcal S_0^{n-1}\times\mathcal S_1 \times\mathcal S_0^{\infty}$. Let us write $X …
Bjørn Kjos-Hanssen's user avatar
2 votes

Covering subset with large probability

It is true. Let $k=\binom{N}{N/2-c\sqrt N}$ and let $K$ be a randomly* selected subset of $k$ of size $k\lambda$. Then conditionally on $|X|>N/2-c\sqrt N$, the difference $|X|-(N/2-c\sqrt N)$ is unbou …
Bjørn Kjos-Hanssen's user avatar
1 vote
Accepted

Finding a distribution satisfying uncountably many constraints. Any relevant references?

It seems that in general this is an almost arbitrarily hard problem. Consider the simpler countably infinite case $X=\mathbb N$, $Y=\{0,1\}$. Thus $H=\{x:h(x)=1\}$ is a "random set". Fix $g:X\to\{0, …
Bjørn Kjos-Hanssen's user avatar
1 vote

Is stopped brownian motion not a martingale?

Let $a=1$ or any other positive constant. Then $$E(M(\inf\{t:M(t)\ge a\}))=a$$ since $$P(M(\inf\{t:M(t)\ge a\})=a)=1.$$ And $a\ne M(t)$ with positive probability (actually probability 1).
Bjørn Kjos-Hanssen's user avatar
0 votes

Minimal coupling

Yes, your bound is optimal and here's how to attain it. Fix a linear ordering $L$ of $\Omega$. Pick a number $x \in [0,1]$ under the uniform measure and the value of our coupling shall be $(M(x),N(x) …
Bjørn Kjos-Hanssen's user avatar
1 vote
Accepted

algebraic tail of a random variable

It just means that $$\mu\left(\{f: K_f>y\}\right)<\frac{\alpha}{y^\beta}$$ and $$\mu\left(\{f: \rho(x_0,f(x_0))>y\}\right)<\frac{\alpha}{y^\beta}$$
Bjørn Kjos-Hanssen's user avatar
5 votes
Accepted

About another potential characterization of normal numbers

Yes, for integer $b$ it's a reformulation of, and exactly the same as, normality to base $b$. Wikipedia even has a section of its article about normal numbers stating exactly this, and giving credit …
Bjørn Kjos-Hanssen's user avatar
2 votes
Accepted

Where does the expected value in the restatement of the pseudoregret come from?

Since $$E(X_{I_t}\mid I_t)=\mu_{I_t},$$ by iterated expectation $$E(X_{I_t})=E(E(X_{I_t}\mid I_t)) = E(\mu_{I_t}),$$ from which we have the desired equality.
Bjørn Kjos-Hanssen's user avatar
1 vote

Are there any continuous-time stochastic processes in which transition probabilities are dis...

One example type is a jump process that jumps at certain predetermined times, as in @AnthonyQuas' comment. For instance, a stock price that can only make jumps when markets open, like New Zealand Sto …
Bjørn Kjos-Hanssen's user avatar

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