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Markov Chain that maximises the entropy creation rate

I am working on MERW (Maximal entropy random walk) for a project. I want to show that given a graph G, there is $\textbf{only one}$ aperiodic markov chain on G that maximises the entropy creation rate ...
ClaraS07's user avatar
8 votes
1 answer
534 views

The cars problem, again

Consider the following simple problem: We are given $2n$ parking spots, labelled from 0 to $2n-1$. There are $n$ cars on the first $n$ spots, and the remaining $n$ spots are free. At every step, every ...
AccidentalFourierTransform's user avatar
0 votes
1 answer
95 views

On the behaviour of individual random walks of a Markov Chain

My current research (on Probabilistic Automaton) brought me to the following question regarding Markov Chains. I state the definitions for the sake of clarity. Let $M$ be a discrete-time finite Markov ...
santi cifu's user avatar
1 vote
0 answers
41 views

Asymptotic mixing time and Euclidean probability distance for path graphs

We are given a simple path graph $P(V,E)$ with vertex set $V$ and edge set $E$, having $n=|V|$ nodes. Given an initial distribution $\mathbf{\mu}$ over $V$, let $d_t(\mathbf{\mu},\pi)$ be defined as $\...
Penelope Benenati's user avatar
2 votes
0 answers
124 views

dimensionality reduction of Markov chains

Suppose that $M$ is a time-homogeneous (and, for simplicity, stationary) Markov chain on $d$ states, which induces the probability measure $P$ on paths of length $n$. I seek a Markov chain $M'$ on $d'&...
Aryeh Kontorovich's user avatar
0 votes
0 answers
66 views

Long-time conditioning for a Markov Chain

I am studying MERW and for some reasons, i would like to know if, if I have $(X_n)$ an irreducible Markov Chain, I can say that $\mathbb{P}(X_1=x | X_0=a, X_n = b)$ goes to $\mathbb{P}(X_1=x | X_0=a)$ ...
ClaraS07's user avatar
2 votes
1 answer
59 views

The ranked mass process associated with a Lambda-coalescent

I am reading a paper by Pitman (1999), and I am confused by his Corollary 7. First some notation so that I can explain my confusion: $\mathcal{P}_\infty$ is the space of partitions of $\mathbb{N}$, $\...
Enforce's user avatar
  • 203
0 votes
0 answers
85 views

Does a 2d random walk hit 0 for increasing distances AND time spans?

Question: For a simple symmetric random walk $(Z_t)_{t\geq 0}$ in $\mathbb{Z}^2$, does $$\lim_{\beta\rightarrow 0}\mathbb{P}^{x_\beta}(Z_t=0\text{ for some }t\leq h(\beta)T)=0\quad (2.8)$$ where $|x_\...
PontyMython's user avatar
3 votes
0 answers
58 views

Infinitesimal generators of random evolutions

Consider two state spaces $X$ and $Y$ and infinitesimal generators of Markov processes $(A_y)_{y\in Y}$ and $B$, on $X$ and $Y$ respectively. We assume that $A_y$ share the same domain $D(A)$, and ...
Gabriel's user avatar
  • 31
1 vote
0 answers
114 views

An urn model with weighted objects and replacement

Consider the following game: In an urn, there are $K$ balls, $x_0$ of them are blue and light (mass $m_0$), $x_1$ are blue and heavy ($m_1$), $x_2$ are red and light ($m_2$), the rest $x_3$ are red ...
PontyMython's user avatar
5 votes
1 answer
192 views

Non-equivalent definitions of Markov process

As far as I know, there are three definitions of Markov processes (or of Markov chains). DEFINITION 1 (WEAKER). A process $(X_t)_{t\in[0,\infty)}$ on $(\Omega,\mathcal{F},\mathbb{P})$ with values in ...
No-one's user avatar
  • 1,149
0 votes
0 answers
101 views

Simulation of Markov processes with exponential timestepping

Let $(Y_t)_{t\ge0}$ be a time-homogeneous Markov process with transition semigroup $(\kappa_t)_{t\ge0}$. Numerical simulation of $(Y_t)_{t\ge0}$ can be done in the following way: Choose an initial ...
0xbadf00d's user avatar
  • 167
1 vote
1 answer
345 views

Random walk on $\mathbb{Z}^3$. Expected number of visits and probability of return

I am working with the simple symmetric random walk on $\mathbb{Z}^3$. Using the Fourier identity I have been able to prove: $$ P(S_n = 0) = \frac{1}{(2\pi)^3} \int_{-\pi}^{\pi} \int_{-\pi}^{\pi} \...
Gonzalo Chiva San Román's user avatar
5 votes
2 answers
369 views

Markov process on a torus with prescribed invariant distribution

In Euclidean space, $\mathbb R^d$, the Langevin diffusion $${\rm d}X_t=b(X_t){\rm d}t+\sigma(X_t){\rm d}W_t\tag1,$$ where $\sigma:\mathbb R^d\to\mathbb R^{d\times k}$, $$b:=\frac{\Sigma+U}2\nabla\ln p+...
0xbadf00d's user avatar
  • 167
0 votes
0 answers
34 views

Does the definition of mixing time work for general non-Markovian processes?

A definition of the mixing time for Markov chains is given by \begin{equation} \tau_{\text{mix}}\equiv\inf{\{t>0: \sup_i\left\vert \frac{\boldsymbol{p}(t|p_j(0)=\delta_{ij})}{\boldsymbol{\pi}}-\...
Richard Ben's user avatar
0 votes
1 answer
180 views

Hidden Markov model with two hidden states?

I am currently studying what Markov models are, and have a question. If we have a hidden Markov model with 2 hidden states or observations, then how do we find the probability of just the main state ...
MarleyMania's user avatar
2 votes
1 answer
123 views

Monotone grand coupling of Markov chains

A stochastic matrix $P$ on a finite poset $(\mathcal X,\preceq)$ is called monotone if $Pf$ is increasing whenever $f$ is. This property ensures the existence of a monotone coupling: specifically, ...
DRJ's user avatar
  • 234
0 votes
0 answers
92 views

MDP Average Reward independent of Initial State

Consider a Markov Decision Process where the state space $S$ and the action space $A$ are continuous and compact. In state $s$, if action $a$ is chosen and the next state becomes $s'$, the ...
Euclid's user avatar
  • 115
4 votes
2 answers
227 views

Given an automatic set $S$ coming from a DFA $M$ when read little-endian, is $\overline{d}(S)$ at most the Büchi acceptance probability of $M$?

Note: I've entirely rewritten this question! Originally it was just the third formulation, take note of that when reading answers. Let's say $S$ is a $b$-automatic set, and let's say $M$ is a DFA ...
Harry Altman's user avatar
  • 2,585
1 vote
1 answer
121 views

Characterization of Fellerian kernels

This question concerns Feller Markov kernels, similar to Vanessa's question. Terminology By 'Markov kernel' $N:E\to F$, we adopt exactly the same definition as Vanessa, with the exception that $E,F$ ...
Hirofumi Shiba's user avatar
2 votes
0 answers
54 views

Including fixed-time transitions into a continuous time Markov chain system

I have system which is mostly described by a CTMC (Continuous-time Markov chain) with a single absorbing state and a large but tractable and sparse transition matrix. However, at a fixed set of "...
Bianca's user avatar
  • 21
0 votes
0 answers
21 views

Proof that Component-wise MH algorithm is invariant w.r.t. target measure

consider a standard situation in Bayesian modelling, given real vector parameter $\theta=(\theta_1,\dotsc,\theta_n)$ and observations $x$ we derive a posterior distribution $\pi$ with posterior ...
MatEZ's user avatar
  • 31
2 votes
0 answers
111 views

Embedding a Markov chain in a Markov process

Let $X_{t\ge 0}$ be a Markov process with values in a metric space $(\mathcal{X},d)$ defined on a probabiltiy space $(\Omega,\mathcal{F},\mathbb{P})$ and let $(\tau_n)_{n=1}^{\infty}$ be a sequence of ...
user521485's user avatar
5 votes
0 answers
271 views

How to play golf in one dimension?

One-dimensional golf is a function $g$ on $\mathbb R$ such that $g(x)= 1+\min_\mu E[g(x+N(\mu,c\mu^2))]$ if $|x|>1$ and 0 if $|x|\le 1.$ Here $N$ is the normal distribution, whose mean $\mu$ you ...
domotorp's user avatar
  • 18.9k
1 vote
1 answer
99 views

Asymptotic variance for averages of trajectory functionals of Markov chain

I am looking for references on theory for convergence rates of ergodic averages of a Markov chain in the more general setting where the functional is over multiple states or even a whole trajectory, ...
itchidese's user avatar
1 vote
1 answer
259 views

Question about the proof of Propp-Wilson algorithm in Olle Häggström's book

Update: Oops! This is a stupid question and should be closed. The definition of the probability space that contains events $A_i$ requires using a single random stream. I have difficulties ...
zemora's user avatar
  • 565
0 votes
0 answers
142 views

Calculating the expected hitting time of a specific birth and death chain

I am working with a specific birth and death chain, defined as follows. Consider a set of states $X = \{0,1,2,...,n\}$, where $x^* \in (0,n)$ is a recurrent state. Transition probabilities are defined ...
Roberto Rozzi's user avatar
3 votes
0 answers
241 views

A few questions on Feller processes

Update. Most of my questions have been answered in the comments. I am adding these answers to the post. There are at least three definitions of Feller semigroup and the corresponding processes: $C_0 \...
tsnao's user avatar
  • 620
2 votes
1 answer
74 views

Conditions for absorption

Let $X$ be a Markov chain with countable state space $S$ and transition kernel $P$, and let $h \colon S \to [0,1]$ be a sub-harmonic or super-harmonic function. Assume that for all $\varepsilon >0$ ...
user avatar
1 vote
1 answer
192 views

Expected time to absorption for Markov chains

Let $X$ be a Markov chain with countable state space $S$ and transition kernel $P$, and let $ T = [ z \in S : \ P(z,z) = 1 ]$. Let $\tau = \inf [ k \geq 0 : X_k \in T ]$ and assume that $ \mathbb{E}^x ...
user avatar
3 votes
0 answers
54 views

Multi-type Galton-Watson-like process where only majority-type is allowed to reproduce

Are you aware of any research papers that have explored a multi-type Galton-Watson process in which only particles of the majority type are permitted to reproduce in each generation? I've been unable ...
Eubos's user avatar
  • 56
0 votes
0 answers
161 views

Markov process with time varying transition kernels

I cross post this question from StackExchange as it may be more appropriate. I am interested in studying the evolution of a variable $\alpha_t\in [0,1]$ governed by the following stochastic dynamical ...
Francesco Bilotta's user avatar
1 vote
0 answers
72 views

Bounding expectation of switching stochastic process

I am analyzing the behavior of an 1D stochastic dynamic system, where the state can vary randomly within a small magnitude. However, when the state deviates too much from zero, its expected magnitude ...
pzr1988's user avatar
  • 11
2 votes
0 answers
237 views

Ball games: How to allocate $N$ balls into $M$ boxes so as to maximize the expected number of taken balls

Consider the following ball games, which looks like very intuitive and simple but I have tried for a long time. Assuming we have $M$ identical boxes and $N$ identical balls, we distribute these $N$ ...
koko's user avatar
  • 21
3 votes
1 answer
190 views

Quantitative version of ergodic theorem in Markov chains

Consider an irreducible Markov chain $X_t$ with finite state space $E$, and unique invariant measure $\pi$. Fix a function $V:E\to\mathbb R$ such that $E_\pi[V]=0$. The ergodic theorem tells us that, ...
Tiago's user avatar
  • 59
9 votes
2 answers
953 views

Direct proof of unique invariant distribution for ergodic, positive-recurrent Markov chain

I posted the following question on MSE, feeling that it perhaps isn't research level mathematics, but didn't get any bites. So, I am crossposting here. The following ergodic theorem is well known. ...
user24601's user avatar
  • 165
2 votes
0 answers
155 views

Can a diffusion process admit an invariant measure with a non-differentiable density?

The precise domain of the generator $A$ of an Itō diffusion on a Hilbert space $H$ (assume $H=\mathbb R^d$, if that's easier for you to work with) can usually not be determined explicitly$^1$. Usually,...
0xbadf00d's user avatar
  • 167
3 votes
1 answer
307 views

"Ergodic theorem" for Markov kernels

Consider a discrete time Markov chain $(X_t)$ on a finite state space $\mathcal{S}$, with transition matrix $P$. Assume that the chain admits a stationary distribution $\pi$, which I will identify ...
Francesco Bilotta's user avatar
1 vote
1 answer
96 views

Asymptotic behavior of a Markov process on the set of $\{0,1\}$-polynomials

This question is cross-posted from https://math.stackexchange.com/questions/4711799/asymptotic-behavior-of-a-markov-process-on-the-set-of-0-1-polynomials I am trying to study the asymptotic behavior ...
Francesco Bilotta's user avatar
1 vote
0 answers
115 views

Concatenation of Markov processes and independence

In chapter 14 of Sharpe's General Theory of Markov Processes the concatenation of Markov processes $X^1$ and $X^2$ is described. I've posed the relevant part at the bottom of this post. It is rather ...
0xbadf00d's user avatar
  • 167
3 votes
1 answer
498 views

Spectral Radius and Spectral Norm for Markov Operators

My question concerns differences between the spectral radius $\rho$ and norm $\| \cdot \|$ of Markov operators in infinite-dimensional Banach spaces. This is far from my area of expertise, that is ...
Sam OT's user avatar
  • 560
2 votes
1 answer
228 views

When is a stationary measure of a Markov chain "exponentially localized"?

Here exponentially localized can be thought in a non-rigorous manner as a measure that is mostly supported on a sparse number of nodes. Some intuition can gained by thinking about a diffusion process, ...
Piyush Grover's user avatar
4 votes
1 answer
247 views

Random walk visiting a cylinder infinitely often

I wonder whether a $d$-dimensional random walk $S_n$, generated by the infinite i.i.d. copies of X given by: $X=e_1=(1, 0, 0, ..., 0)$ (with probability $p_1$) $X=e_2=(0, 1, 0, ..., 0)$ (with ...
Hamid Enki's user avatar
1 vote
0 answers
48 views

Sample complexity of estimating a doubly stochastic matrix

Let $P\in\mathbb{R}^{n\times n}$ be a doubly-stochastic matrix. That is: $$P(x,y)\geq 0,\quad \sum_xP(x,y)=1,\quad \sum_yP(x,y)=1.$$ I would like to know if lower and upper bounds on the sample ...
user134977's user avatar
3 votes
1 answer
340 views

Importance resampling with exponential weighting

Suppose that we have $$ \frac{p(x)}{q(x)} \propto \exp(\tau f(x)), $$ where we can sample from $q$ but not from $p$. Our goal is to generate a set of particles $\{x_i\}_{i=1}^n$ such that $n^{-1}\sum_{...
Minkov's user avatar
  • 1,127
3 votes
2 answers
277 views

Is there something like a "self-avoiding Markov chain" on a continuous space?

If stumbled accross self-avoiding walks. They seem to be deterministically generated, but from a quick google search term seem to be randomly generated variants. However, as far as I can see they are ...
0xbadf00d's user avatar
  • 167
2 votes
1 answer
201 views

Joint irreducibility and aperiodicity of two independent Markov chains

Let $(X_i)_i, (Y_i)_i$ be two independent Markov chains on Polish state spaces $\mathcal{X}, \mathcal{Y}$ and with kernels $P, Q$. Suppose that they are both $\psi$-irreducible and aperiodic and have ...
Dasherman's user avatar
  • 203
0 votes
1 answer
205 views

Inhomogeneous Markov chains and the product-integral as a solution to the Kolmogorov forward equation

We have a inhomogeneous continous $K$-State Markov chain $X(t)$ with transition intensity matrix $Q(t)$. Therefore its entries are: $$q_{ij}(t)= \lim_{\delta \to 0} \frac{1}{\delta} \mathbb{P}(X(t+\...
Bloble's user avatar
  • 3
2 votes
0 answers
57 views

Right spectral gap of vector of two independent Markov chains

Let $(X_i)$ be a stationary Markov chain on $S$ (a potentially uncountable space with a Borel sigma algebra) with stationary distribution $\pi$ and transition kernel $P$. Let $(Y_i)$ be a stationary ...
Dasherman's user avatar
  • 203
2 votes
2 answers
302 views

Polynomial time mixing Markov chain for multimodal distribution

Is there a discrete space Markov chain, starting from a fixed state, whose stationary distribution is a multimodal distribution and that mixes in polynomial time? For example, Ising model on say a ...
voila's user avatar
  • 201

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