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3 votes
2 answers
973 views

How much larger than the relaxation time can the mixing time be?

The notation is mostly taken from the book "Markov chains and mixing times" by Levin, Peres, and Wilmer. Consider an irreducible, aperiodic, time-reversible, discrete-time Markov chain on a finite ...
Hedonist's user avatar
  • 1,269
1 vote
0 answers
44 views

Validating a probability density distribution forecast model for a Markov process

Let's say we have a Markov process $X_t$, and we come up with a forecast model that takes some information from outside world and says: "value $X_{t+1}$ has probability density distribution $P_t(x)$". ...
mt_christo's user avatar
0 votes
0 answers
117 views

Ergodicity property for continuous-time Harris positive Markov process

I have posted this question on there, but got no answer. The following theorem is Theorem 13.3.3 of Meyn and Tweedie's Markov Chains and Stochastic Stability on page 328: Theorem 13.3.3. If $\Phi$ ...
Danielsen's user avatar
  • 109
1 vote
0 answers
101 views

How to fit a stochastic matrix to given data.?

Given a data sequence of noisy observations of a 3-state Markov chain $X$ -- $y_1$,$y_2$,...$y_n$, with two transition matrices $A_1$ and $A_2$ corresponding to different regions (**) in the (unit) ...
inherited_knowledge's user avatar
1 vote
0 answers
111 views

Conditional probabilities in epidemic model

I was contemplating an epidemic model where infection and recovery rates are determined by links. Here node $i$ is infected first and recovers at a rate $\mu_i$. For all other nodes, the recovery is ...
Bravo's user avatar
  • 519
6 votes
1 answer
509 views

Approximating Markov chains by Brownian motion

I would like a result along the following lines to be true, but haven't been able to locate it in the literature; pointers would be welcome. Let $X_{t}$ be a finite-state, irreducible, aperiodic ...
Elena Yudovina's user avatar
12 votes
3 answers
4k views

How to explain "Feller process" to an undergraduate student?

I had to explain in informal terms what a Feller process was, to undergraduate students who understand Markov property, Poisson processes and such. It was easy to define Levy process as generalisation ...
Bravo's user avatar
  • 519
6 votes
2 answers
912 views

References for a physicist migrating to stochastic processes

I've studied "Markov Chains" - Norris and "Measure, Integral and Probability" - Capinski, Kopp. Now, I'm looking for a couple of books (or other references) that help me bridging these two topics. ...
edwineveningfall's user avatar
8 votes
4 answers
1k views

Invariant measure of Euler-Maruyama Discretisation of an Ito diffusion

Let $(X_t)_{t \geq 0}$ be a diffusion process with dynamics governed by the stochastic differential equation \begin{equation} dX_t = b(X_t)dt + \sigma(X_t)dW_t, ~~ X_0 = x_0, \end{equation} where $b,\...
Sam Livingstone's user avatar
3 votes
0 answers
305 views

Nonlinear Markov process

Consider the following nonlinear $\mathbb{R}$-valued stochastic recursive sequence: $ X_{n+1} = F(X_n) + W_{n+1}, \quad (W_n)_{n\ge1} \stackrel{ \scriptsize \mathrm{i.i.d.} }{ \sim } \phi. $ How can ...
user47855's user avatar
0 votes
1 answer
408 views

Generating independent random variable from two correlated random variables

Suppose two random variables $X$ and $V$ are given. I am wondering what kind of condition we need to impose on joint distribution of $V$ and $X$ to make sure that there exists a random variable $Z$ ...
math-Student's user avatar
  • 1,109
2 votes
0 answers
199 views

CLT for a Markov Renewal Process

Suppose $(X,T)=\{(X_n,T_n)\}_{n\geq0}$ is a Markov renewal process, where $X$ is a finite-state, discrete-time Markov chain with state space $\{1,2,...,R\}$. $T$ is the additive component, more ...
MthQ's user avatar
  • 41
6 votes
1 answer
387 views

Quasi-stationary distribution for a death process

In the paper, Survival in a quasi-death process by van Doorn and Pollett, the quasi-stationary distribution of a transient CTMC is discussed and QSD for a simple death process is derived. Consider a ...
Bravo's user avatar
  • 519
2 votes
1 answer
665 views

Transition probabilities in coupled Markov chains

I know that for a continuous-time Markov chain, the probability of transition from time $0$ to $t$ is given by $P(t)=e^{Q(t)t}$. I have a system of $N$ interdependent continuous-time Markov chains ...
Bravo's user avatar
  • 519
6 votes
1 answer
171 views

Relative vulnerabilities in SIS epidemic model

Consider the SIS model of epidemic spreading. There is a finite graph $G(V,E)$, link infection rates $\lambda_{ij}$ and node recovery rates $\mu_i$. There are a few initial nodes which are infected at ...
Bravo's user avatar
  • 519
1 vote
1 answer
687 views

Supremum in a Markov chain model

A Markov chain $X$ with finite state space $\{1,2,\cdots,N\}$ is defined on a probability space $(\Omega, P, \mathcal{F})$ equiped with filtration $\{\mathcal{F}_t\}$. And we assume that we can reach ...
Max's user avatar
  • 21
3 votes
4 answers
681 views

Does the variance of a continuous time, time homogeneous, Markov process starting from one point necessarily not decrease?

Let $x_t$ be a zero mean, time homogeneous Markovian process (chiefly look at the case where the value is in $1$ dimension) over time $t$ starting from $x_0=0$. Is it necessary that, in continuous ...
Hans's user avatar
  • 2,239
1 vote
0 answers
196 views

The problem of the drunkard in a valley [closed]

We consider a Markov chain on a subset of positive integers S = {0, 1, 2, 3, .......N}, with transition probabilities defined as follows: The chain jumps only one unit to the left or right. p(i, j) =...
Cristian Dumitrescu's user avatar
4 votes
0 answers
264 views

Generalized Markov Processes on CW complexes of dimension > 1

Markov processes have a large variety of applications to physics and chemistry (as well as many other fields). Such processes are formulated on graphs, i.e., CW complexes of dimension one. It is ...
John Klein's user avatar
  • 18.8k
0 votes
1 answer
2k views

Markov Chain: state reduction

Hi I am trying to understand a proof in a paper (written by Isaac Sonin), I don't know if anyone could give me a clarification on the following: Firstly we have a Markov chain $\{Y_k\}$ with finite ...
Cal's user avatar
  • 23
4 votes
0 answers
282 views

Markov operators and existence of ergodic measures

My question refers to the yesterday's question (see here) of John Learner and goes as follows: Can we deduce the existence of an ergodic measure if we know that an invariant measure exists, but the ...
Almost sure's user avatar
0 votes
0 answers
151 views

Inequality relating stationary probabilities and transition probabilities

Let $P$ be the transition probability matrix of a aperiodic irreducible DTMC and let $\pi$ be its stationary distribution. I would like to know if there is any literature on types of Markov chains ...
Vedarun's user avatar
  • 23
1 vote
1 answer
293 views

Empirical distribution of a collection of iid Markov chains

Suppose we have $N$ independent 2-point Markov chains each having a rate matrix $Q = [-1,1;1,-1]$ and stationary distribution $\pi = [0.5,0.5]$. At time $t=0$, we initiate the chains so that the ...
VSJ's user avatar
  • 1,034
3 votes
1 answer
2k views

Hitting time probability in a Random Walk with possibility to die.

A Random Walker can move of one unit to the right with probability $p$, to the left with probability $q$ and it can jump again to the starting point with probability $r$ and die. Naturally $p+q+r=1$. ...
QuantumLogarithm's user avatar
2 votes
1 answer
421 views

Extending Wald's equation to two classes of i.d. random variables?

I try to adopt Wald's equation to a slightly more complex problem. In fact, after a full day, I found some solution now, but it has a confusing argument in the middle. Perhaps somebody can help me at ...
cubic lettuce's user avatar
14 votes
2 answers
2k views

Markov chains: invariant measures and explosion

The following seems like such an elementary question, but I didn't get anywhere with it. Suppose you are considering a Markov chain in continuous time which is transient and has an invariant measure (...
Nathanael Berestycki's user avatar
2 votes
1 answer
447 views

MCMC with progressive demollification of delta distributions

Edit: I simplified the example to a canonical case for clarity. Given an integral $\int_{\Omega}{g(\mathbf{x})}$ with a well-posed integrand $g(\mathbf{x})$ defined on some multidimensional space $\...
4 votes
0 answers
1k views

The spectrum of a Markov Operator and Invariant Measures

Suppose I have a discrete-time Markov Chain (in an infinite dimensional state space $\Omega$) with Markov operator $P$, a linear operator on the space of bounded measurable functions on $\Omega$. (Or ...
Jeremy Voltz's user avatar
3 votes
1 answer
335 views

Stochastic processes having Markov kernels

Let $(\Omega_1, \mathcal{F}_1, P_1)$ and $(\Omega_2, \mathcal{F}_2, P_2)$ be probability spaces and suppose $(X_t)$ and $(Y_t)$ are real-valued stochastic processes defined on the respective spaces. ...
Biswarup Das's user avatar
4 votes
2 answers
835 views

Reference on continuous-time finite state filtering

Problem: I'm working in reliability field and have seen papers written on the topic like process of failures when systems are functioning under unobservable (or observable) Markov-like environment, i....
Tomas's user avatar
  • 267
3 votes
1 answer
1k views

Ergodicity of a Markov chain

Hi, I'd appreciate some help on a Markov chain result I'm trying to show. I believe the following is sufficient for a continuous time Markov chain $(X_t)$ with a countable state space to be ergodic: ...
A Chuh's user avatar
  • 181
2 votes
1 answer
395 views

Probability-one event for Markov chain

Let $X$ be a Markov chain, with countable state space $I$ and transition probability matrix $P$. $X$ is irreducible, but need not be recurrent. Let $S$ be a fixed subset of $I$. Define a subset $K$ ...
Elena Yudovina's user avatar
11 votes
1 answer
642 views

Random walk origin return monotinicity

Consider a Markov chain on $\mathbb{Z}^d$ with transition kernel $P$ for adjacent vertices (non-diagonal). Essentially this is a $d$ dimensional random walk with the probability of a transition ...
Alex R.'s user avatar
  • 4,952
2 votes
2 answers
861 views

Spectral gap of a product of Markov processes

For $m \in [N] \equiv \{1,\dots, N\}$, let $Q^{(m)}$ be the generator of a (well-behaved) continuous-time Markov process on a finite state space $[n_m]$. Write $J \equiv (j_1,\dots,j_N) \in \prod_m [...
Steve Huntsman's user avatar
3 votes
3 answers
1k views

Markov random field with continuous index set

Hi There's Markov random field (MRF) which, by my Wikipedia-based knowledge, is an extension of Markov chain. I'd like to think of it as going from 1D to higher dimensional spaces. Inherent in its ...
Mahdiyar's user avatar
  • 355
2 votes
2 answers
1k views

Borel-Cantelli Lemma on MCs (absorbing states)

hi, I'm sorry if the question is silly, but I couldn't get my head around it for a while now. In Markov Chains (MC) proving that a state is either recurrent or transient is through Borel-Cantelli ...
sigma_z_1980's user avatar
2 votes
2 answers
1k views

Counterexample Markov process

Let $X$ be a homogeneous Markov process in a continuous time with value in the set $E$. Suppose that for some $T>0,x\in E, A\subset E$ we have $$ P_x[X_t\in A] = 0 $$ for all $t\in [0,T]$ but $$ ...
SBF's user avatar
  • 1,655
2 votes
1 answer
640 views

Reachability for Markov process

Let $X$ be a Markov process (in continuous or discrete time) and define an event $$ R(T,A) = (\exists t\leq T: X_t \in A). $$ I have seen in one paper that $$ \Pr[R(\infty,A)] = \sup\limits_{\tau} \...
SBF's user avatar
  • 1,655
2 votes
1 answer
186 views

scalar diffusions are reversible

It is well known that under mild assumptions a scalar diffusion $dX_t = a(X_t) dt + \sigma(X_t) dW_t$ with invariant probability distribution $\pi$ is reversible. This is indeed not true for ...
Alekk's user avatar
  • 2,133
4 votes
1 answer
782 views

A simple problem in markov chains

I'm trying to understand a 1954 paper of Kubo intitled "Note on the stochastic theory of resonance absorption". The specific problem can be stated mathematically as follows: let $X(t)$ be a random ...
The man in the box's user avatar
8 votes
4 answers
8k views

Is there MDPs (Markov Decision Process) which have a non deterministic optimal policy?

I'm working on Markov Decision Process and I have not found yet an example of MDP that has a stochastic (non deterministic) optimal policy. Is there MDPs that have a stochastic optimal policy or is it ...
Lamine's user avatar
  • 254

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