A stochastic process satisfying the Markov property: the distribution of the future states given the value of the current state does not depend on the past states. Use this tag for general state space processes (both discrete and continuous times); use (markov-chains) for countable state space ...

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Markov chain problem with finite states

Consider any Markov chain on a state space with exactly $r$ states. We want to find the largest $N>0$ such that there exists states $i,j$ for every $n < N$ we have $p_{ij}^{(N)} > 0$ and ...
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Stochastic processes with independent increments

If $\{X_{t}:t\geq 0\}$ is a real-valued stochastic process with independent increments then $\{X_{t}:t\geq0\}$ is a Markov process? Let $\{ \mathcal{F}_{t} \}_{t\geq0} $ be a natural filtration of ...
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Markov Chain depicting unruly customer behavior

A store has 2 bins of balls. 1 bin is red, and contains 3 red balls. The other bin is gray and contains 2 gray balls. Every minute, on the minute, exactly one customer comes by the bins, picks up ...
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Strong Markov property of Brownian motion

I was able to understand Brownian Motion $\{B(t):t\geq0\}$ has Strong Markov Property i.e. For any stopping time $\tau$, $P(B(t+\tau)\leq y | \mathcal{F}_{\tau})=P(B(t+\tau)\leq y|B(\tau))$ a.s. , $y ...
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Calculation of the Gallavotti-Cohen fluctuation theorem made by Lebowitz

I have a problem understanding a calculation in this paper (another form of the theorem an be found here at equation 11). For those who want to read the paper, I have difficulties with formula 2.14 in ...
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Consider a Stochastic process X which moves between the corners of a regular tetrahedron. Find P(Xn = 1)

Consider a Stochastic process $X$ which moves between the corners of a regular tetrahedron. The process starts at time 0 in node 1. At each time step, the process chooses an one of the connected edges ...
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Random walk where increment depend on current position

Consider the following stochastic process, $$b(i+1) = b(i) + \xi_i (b_i),$$ where $\xi_i(b_i) \in \{-1, k \}$ are the independent increments having the following distribution: $$\begin{align} P (\xi ...
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Library chain stationary distribution

This is an exercise 1.47 from Richard Durrett's Essentials of Stochastic Processes p.85 (doi: 10.1007/978-1-4614-3615-7_1 or Google Books). On each request the ith of the $n$ possible books is the ...
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61 views

Poisson Process (Easy)

I'm stuck at the following question: Customers with items to repair arrive at a repair facility according to a Poisson process with rate λ. The repair time of an item has a uniform distribution on ...
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Markov chain simulation

I'm wonder if there is an algorithm to simulate a discrete Markov chains with a specific number of occurence of state knowing the transition matrixway. For example, how to simualte in $\mathbb R$ a ...
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185 views

Equivalence Classes of a Markov Chain with Transition Matrix

I have the following transition probability matrix for a markov chain with state space S={0,1,2,3,4,5,6}: $\begin{bmatrix} \frac13 & \frac13 &0 & 0 & \frac16 & 0 & \frac16\\ ...
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random walk in a certain environment

Consider the following random walk in one dimension, starting from $r(0)=0$. $$ r(i+1) = r(i) + \xi, $$ where $\xi(i, r(i))$ is an increment with distribution $P(\xi=1) = \frac{c^{r(i)}}{i-r(i)+1}$ ...
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Probability of a sequence of events in a Poisson process.

I am starting to study Poisson processes and I came up with this question: Let there be two Poisson processes with rates $\lambda$ and $\mu$ respectively, monitoring the occurrence of events (e.g. ...
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29 views

Prove equilibrium theorem without irreducibility and aperiodicity

I have to solve the following question: Consider a random walk Markov chain on $S = \{1, 2, \ldots, 100\}$. If the chain is between 2 and 99, it selects one of the adjacent states with equal ...
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302 views

Markov chains: is “aperiodic + irreducible” equivalent to “regular”?

I have two books on stochastic processes. In one book, it says that the limiting matrix is possible to find if the matrix is regular, that is, if for some $n$ $P^n$ has only positive values. The ...
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25 views

Markov Decision Process - Optimal policy invariance to scaling in the Utility Function

The title says it all. If i use a discounted Utility Function, why is the optimal policy invariant with respect tot the scaling of the Utility Function by a positive Factor?
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A theorem in the paper “Noncommuting Random Products” by Furstenberg

I have a question concerning the proof of theorem 2.5 at page 395 of the paper Noncommuting Random Products, by H. Furstenberg, Trans. Amer. Math. Soc., 1963. The statement is as follows: Let $\mu$ ...
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What does stationarity of the point process entail in a Markovian setting?

Let $(\Omega,\mathcal{F},P)$ be a probability space where $\Omega$ is the set of cadlag trajectories from $\mathbb{R}$ to a countable state space $S$. Let $X$ be the coordinate process $X_t(\omega) = ...
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Log-likelihood function

I'm not sure if this could be asked here, or in math overflow... In the following paper Cho, Jin Seo, and Halbert White. "Testing for regime switching." Econometrica 75.6 (2007): 1671-1720. doi: ...
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MDP problem - How is the expected cost calculated?

I have been stuck with a problem for a while regarding Markov Decision Processes for a Policy improvement algorithm. Assume that I have probabilities for certain states to evolve the system into, ...
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194 views

Equivalent defining Markov property

Consider the stochastic process $(X_t)_{t \in \mathbb{R}}$ and show the equivalence of the following two Markov properties: (a) $P(X_t \in A \mid X_u, u \leq s) = P(X_t \in A\mid X_s) \qquad ...
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56 views

Strong Markov property given transition functions

Suppose we are given family of transition functions satisfying Chapman-Kolmogorov equation, what conditions will ensure that there exists a continuous or cadlag Markov process with given transition ...
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State Space Difference Linear Dynamic System

I am interested in finding the DIFFERENCE in the state space distributions for two linear dynamical systems (System A and System B). I am able to solve for this using the matrix exponential. But the ...
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79 views

transition matrix for Markov chain

Can any one help me to solve this home work please? The city of Sacramento recently completed a new light rail system to bring commuters and shoppers into the downtown area and relieve freeway ...
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55 views

Estimate the probability using Markov chains

please consider this question: A study using Markov chains to estimate a patient's prognosis for improving under various treatment plans gives the following transition matrix as an example ...
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65 views

Stationary distribution for a Markov chain which is not irreducible

I have a Markov chain with $K$ states $S$: {$s_1,s_2,...,s_K$}. $s_1$ is reachable from any state in $S$; however not all the states can be reached from $s_1$. What does the stationary distribution ...
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Does time homogeneity imply strong Markov property in a Markovian process

Does a time homogeneous Markovian process necessarily have strong Markovian property? Does continuity in state space, time, or path make a difference? What are the examples if it does not?
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Examples of decreasing-in-some-time-interval variance of a time homogeneous Markovian process

Let $x_t$ be a zero mean, time homogeneous Markovian process over time $t$ starting from $x_0=0$. What are the examples of $x_t$ where the variance at $t$ decrease over some interval of $t$? The ...
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186 views

Proof that Markov Chains converges to the stationary distribution

Let $P$ is a transition matrix of a Markov Chain, which is irreducible, aperiodic and lets assume $\pi$ is its stationary distribution: $\pi = \pi P$. Does anyone knows the proof for the following ...
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Probabilistic event triggered on a Markov Process transition

I would like to assess a system disponibility using a Markov Process. This system has two states : a functionning state 0 and a failure state 1, with a fault rate $\lambda$ and a mean time to repair ...
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36 views

Exsistence and uniqueness of stationary density for Markov Chain

Suppose we're given a function $f:\mathbb{R}^2\to\mathbb{R}$. We define a Markov Chain $(X_n)$ by \begin{align} X_0&\sim f_X, \\ X_n&=f(X_{n-1},Y_{n-1}), \end{align} where $(Y_n)$ is a ...
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Asymmetric Markov process

The limiting distribution $\xi(x)$ of a Markov process $$x_0=1\text{ and }x_{i+1}=x_i+\Delta x_i,\tag1$$ where $\Delta x_i=-ax_i$ and $\Delta x_i=a$ occur with equal probability for every $i$, and ...
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Markov operators

Transition probability functions can always be used to generate Markov operators, correct? So is it correct to say that a Markov process is a collection of Markov operators? On the other hand, are ...
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How to prove theorem about consistency of Markov edge process?

How to prove such theorem: Markov edge process $p_E(y_E)$ with respect to DAG $G=(V,E)$ defined as $p_E(y_E) = \prod_{v \in V} p_E\left(y_{E_{\rm out}(v)} \,\big|\, y_{E_{\rm in}(v) } \right) = ...
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Help With Eigenvectors and Dynamical Systems

I have the following system of differential equations: $ \frac{d}{dt} \left[ \begin{array}{c} A(t)\\ N(t)\\\end{array} \right] = \left[ \begin{array}{c c} -(a+b) & 0\\ a & -(a+b)\\ ...
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First and second moments of recurrence time in a finite two-dimensional Markov chain

I have a two dimensional finite Markov chain with $(m+1)^2$ states, and with transition rates: $q_x((x,y)\to (x+1,y))=(m-x)\lambda,\quad 0\leq x< m, 0\leq y \leq m$, $q_x((x,y)\to ...
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Markov chain and hitting times

I have a Problem about hitting times. That's the following: Let $A\subset E$ and the first passage time $T_A$ and the hitting time $H_A$. Define: $T_A =\inf\{n\geq 0;X_n \in A\}$ and $H_A ...
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Steady state distribution for Markov pure jump process

Assuming an irreducible, positive recurrent Markov Pure jump markov process with state space, $S={0,1}$ The embedded Markov Chain which is doubly stochastic (i.e) columns and rows of the transition ...
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Calculating cumulative Markov Chain outcomes

I have a Markov process, with 2 possible states (1 or 0) and a transition matrix P. State at time t=n is determined by x0*Pn. As n goes to infinity, xn goes to the steady state vector, q = [q1 q2]. ...
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transition kernel

I've got some trouble with transition kernels. We look at Markov process with statspace $(S,\mathcal{S})$ and initial distribution $\mu^0$. We have a transition kernel $P:S\times ...
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Does a Markov Blanket allow connections between Parents of a Node?

In a Markov Blanket, we can connect the childredn of a node between them, as a child can be parent (or spouse) of another child. Does this rule apply as well for Parents of a node? In advance, Thank ...
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Find Markov policy that minimizes(maximizes) the expected discounted cost(reward)

It's an exam problem I found online.Here's a link to the pastpaper. The problem is stated as follows. A repairman who services Q facilities moves between location s and location j according to the ...
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1answer
117 views

What is the difference between positive presistent and null persistent state in a Markov Chain?

I'm not looking for the difference in the mathematical definition, but rather for an intuitive explanation of their differences and possible examples, so that I can have them in my head when ...
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Markov Chains Proof using Statistics

Source: This came from "Introduction to probability" by Charles Miller Grinstead, and James Aurie Snell. It was located on page 407 and is Theorem 11.1 in the section 11.1 Introduction. Theorem: The ...
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Transition function is a Markov semigroup?

How does the transition function in a Markov process become a Markov semigroup in time homogeneous Markov processes? Thanks a lot.
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Question on the proof of the simple Markov property of a Brownian motion

Today we proofed the (simple) Markov property for the Brownian motion. But I really don't get a crucial step in the proof. The theorem states in particular that for $s\geq0$ fixed, the process ...
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makov chains and property

let $X_t$ for $t \in \{1,2,...,10\}$ be a sequence of independent tosses of a fair coin. We denote heads with 1 and tails with 0. Define the random variable $S_n=\sum_{t=1}^n X_t$ for $n \in ...
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Markov time $ T= \min\{n : X[n] = 1\}$

Let $T$ is a Markov time such that $T= \min \{ n : X[n] = 1\}$ , $X[n]$ is the number of $h$ (heads) in coin tossing for $n$ times. Let's say I will toss the coin 3 times, so the event collection is ...
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Proof for a Markov process example (using measure theory)

Consider the probability space $(\mathbb{R},B(\mathbb{R}),\delta_x)$ for a given $x\in\mathbb{R}$ (where $\delta_x$ is the Dirac measure) and define the process $X_t(\omega)=\omega - t$, for $t\geq ...
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How to Prove by definition, the given process is a Markov Process?

Define the process Xt by X0 = 1, and for t = 1, 2, . . . Xt = { uXt-1, with probability p, { vXt-1, with probability 1-p where 0 < v < 1 ...