Stochastic processes (with either discrete or continuous time dependence) on a discrete (finite or countably infinite) state space in which the distribution of the next state depends only on the current state. For Markov processes on continuous state spaces please use (markov-process) instead.

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Equilibrium distributions of Markov Chains

I often get confused about when a Markov chain has an equilibrium distribution; when this equilibrium distribution is unique; which starting states converge to the equilibrium distribution; and ...
15
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1answer
575 views

Eigenvalues for $3\times 3$ stochastic matrices

This is a plot of the non-real eigenvalues of 10000 randomly generated $3\times3$ stochastic matrices. It's pretty clear that they lie in the convex hull of the three cube roots of unity. The ...
4
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0answers
146 views

6-digit password - a special decoding method

Consider the situation of decoding a 6-digit password that consists of the symbols A to Z and 0 to 9, where all possible combinations are tried randomly and uniformly. Consider the ...
2
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1answer
2k views

Irreducible, finite Markov chains are positive recurrent

I am under the impression that an irreducible, finite Markov chain is necessarily positive recurrent. How might I show this? Regards, Jon
5
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1answer
537 views

Probability distribution for the position of a biased random walker on the positive integers

I initialize a biased one-dimensional random walk on the positive integers at the origin, $x = 0$, which also serves as a reflecting boundary blocking steps onto the negative integers. Let's say that ...
13
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2answers
3k views

Nice references on Markov chains/processes?

I am currently learning about Markov chains and Markov processes, as part of my study on stochastic processes. I feel there are so many properties about Markov chain, but the book that I have makes ...
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3answers
4k views

What is the difference between all types of Markov Chains?

I have been looking for some good material covering Markov Chains but everything seems so difficult to me... After reading about the subject, I figured out that there is basically three kinds of ...
4
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1answer
267 views

Conditional return time of simple random walk

Consider a simple symmetric random walk on $\mathbb{Z}$, $(S_t)_{t \geq 0}$. Call $\tau_k = \min\{t \in \mathbb{N}\, : \, \, S_t =k \}$, the hitting time of $k \in \mathbb{N}$. Call $\tau^* = \min\{t ...
3
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1answer
2k views

Calculating stationary distribution of markov chain

I am asked to compute the stationary distribution of the markov chain with state space $E=\{0\dots,n\}$ and transition matrix below: \begin{bmatrix} 0 & 1 \\ \frac{1}{n} ...
3
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2answers
431 views

How can I compare two Markov processes?

There is a discrete-time irreductible Markov process with $r$ possible states. $k$ observations were performed. At each observation a state of process was determined. $T_0 = \lbrace 0,1,\dots ...
1
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1answer
54 views

Symmetric random walk and the distribution of the visits of some state

I need help with this problem: Let $(S_n)_n$ a symmetric random walk in $\mathbb{Z}$ i.e $S_n=X_1 + \cdots + X_n$ with $(X_n)$ iid $\mathbb{P}(X_n=1)=\mathbb{P}(X_n=-1)=\frac{1}{2}$. Let $m \in ...
1
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2answers
798 views

Perron-Frobenius theorem

In the proof of the Perron-Frobenius theorem why can we take a strictly positive eigenvector corresponding to the eigenvalue $1$? Before that, why can we even take a non-negative eigenvector? Books ...
4
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2answers
421 views

How can a Markov chain be written as a measure-preserving dynamic system

From http://masi.cscs.lsa.umich.edu/~crshalizi/notabene/ergodic-theory.html irreducible Markov chains with finite state spaces are ergodic processes, since they have a unique invariant ...
3
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3answers
147 views

Characterize stochastic matrices such that max singular value is less or equal one.

By a stochastic matrix, I mean any non-negative square real matrix with rows summing to one. It is well-known that singular values of stochastic matrices can be more than one. Is there a ...
2
votes
2answers
206 views

Transition Matrix eigenvalues constraints

I have a Transition Matrix, i.e. a matrix whose items are bounded between 0 and 1 and either rows or columns sum to one. I would like to know if it is possible that in any such matrices the ...
3
votes
2answers
380 views

Expectation of a stopping time uniquely determined by a function

Let $(X_t)_{t\ge0}$ be a Markov chain on a finite state space $\Omega$, with transition probability $P$. Let $T$ be a stopping time such that $T=\min \{t\ge 0;X_t \in A \subset \Omega \}$.  If ...
2
votes
2answers
429 views

Finding the exact stationary distribution for a biased random walk on a bounded interval

Imagine we have a biased random walk on an interval $[0, L]$, where the probability of taking a $+1$ step is $p$ and the probability of taking a $-1$ step is $(1-p)$. At the reflecting boundary $0$, ...
2
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1answer
459 views

Finite State Markov Chain Stationary Distribution

How does one show that any finite-state time homogenous Markov Chain has at least one stationary distribution in the sense of $\pi = \pi Q$ where $Q$ is the transition matrix and $\pi$ is the ...
1
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2answers
62 views

$(S_0+\ldots + S_n)_{n\geq 0}$ not a Markov chain

Assume that $Y_0,\ldots , Y_n$ are independent random variables with the following identical distribution: $Y_i=1$ with propability $p$ and $Y_i=0$ with propability $1-p$. Also set $S_0=0$ and ...
1
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1answer
116 views

Markov Chain transitional probability query.

Say I have the transitional probability matrix P= $\begin{bmatrix}.8 & .2\\.6 & .4\end{bmatrix}$ And the entry (1,1) denotes the probability that I stay in state 0, (1,2) I move from state 0 ...
0
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0answers
58 views

Show that every finite closed class is positive recurrent

Let $C$ be a finite closed class. Prove or disprove that $C$ is positive recurrent. Note 1: In our lecture we proved that every finite closed class is recurrent. Note 2: (Positive) recurrence is ...
0
votes
1answer
390 views

Random walk with single absorbing boundary

There is a random walk on a linear lattice of size $\{0,N\}$, where $0$ is the origin and a reflecting boundary and $N$ is the absorbing boundary. It moves forward or backward one step at a time with ...
0
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1answer
128 views

Determining computational complexity of stochastic processes

I have an program which implements a Markov chain Monte Carlo process on a system of N bits, stopping when the process converges. Let's use T to denote the average number of steps made by the Markov ...
17
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5answers
4k views

Good introductory book for Markov processes

Which is a good introductory book for Markov chains and Markov processes? Thank you.
10
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2answers
948 views

Expected number of turns for a rook to move to top right-most corner?

Suppose a rook starts on the lower left-most square of a standard $8 \times 8$ chess board. The board contains no other pieces. The rook randomly makes a legal chess move with every turn (directly ...
5
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2answers
226 views

Generalization of the Jordan form for infinite matrices

Under what conditions is it the case that for a matrix $M$ whose rows and columns are indexed by a countably infinite set $S$ one has a Hamel basis consisting of generalized eigenvectors (i.e. $v \in ...
4
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2answers
102 views

When are stable continuous time Markov chains Feller? Always?

This is a question is similar to this 2 year-old one that never got answered (truthfully it's pretty much the same question except that I'm adding a bit more detail and the assumption that the $Q$ ...
2
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1answer
401 views

If $P$ is a regular transition probability matrix then $P^{n^2}$ has no zero element

A transition probability matrix $P\in M_{n\times n}$ is regular if for some $k$ the matrix $P^k$ has all of its elements strictly positive. I read that this can be tested by using the following ...
6
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2answers
172 views

What does it mean to observe a Markov Chain after a certain kind of transition?

I'm working on a problem concerning censoring of transitions in a Markov Chain. For example, take a Markov Chain that models a counter, it goes up or down but does not stay in position. A possible ...
5
votes
1answer
137 views

recurrence criterion for random-walk like Markov chain

Suppose we have a random-walk like Markov chain, i.e. state space is the set of all integers from $-\infty$ to $\infty$, the transition probability $P_{ij}$ is nonzero only when $j=i+1$ or $j=i-1$. ...
5
votes
2answers
4k views

Is ergodic markov chain both irreducible and aperiodic or just irreducible?

As I find some definition says: Ergodic = irreducible. And then Irreducible + aperiodic + positive gives Regular Markov chain. A Markov chain is called an ergodic chain if it is possible to go ...
5
votes
1answer
245 views

Does every continuous time minimal Markov chain have the Feller property?

Consider a Q-matrix on a countable state space. (A Q-matrix is a matrix whose rows sum up to $0$, with nonpositive finite diagonal entries and nonnegative offdiagonal entries). As explained for ...
4
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1answer
194 views

Combinatory + Coding Theory

I am reading about an algorithm for finding minimum-weight words in large linear codes. Let $c$ be the codeword of weight $w$ to recover (with size $n$ and in $GF(2)$). Let $N = \left\{1, 2, \ldots, ...
4
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1answer
286 views

question involving Markov chain

Let $S_{2m}$ be the group of all permutations $\pi$ of $\{1, 2, \ldots, 2m\}$. The following transition kernel $S$ generates the random transposition walk $$ Ch(\pi, \pi')= \begin{cases} \frac{1}{2m} ...
4
votes
1answer
4k views

How can I compare two matrices?

I have a matrice A. It is model probability matrice for some process (Markov chain). Then, I have estimated matrice B. I have to somehow compare these two matrices to tell whether process that gave ...
3
votes
1answer
281 views

Expected number of runs

Let $S[16]$ be a binary array i.e, elements of $S$ are 0/1 with elements $S[i]$ are taken uniformly and independently form $\{0,1\}$. Let $k$ be a random element taken uniformly from $\{0,1\}$. I have ...
2
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1answer
39 views

On track Prerequisite for Statistics and Probability

I do not really have a solid mathematical background because of the range of courses i had back in high school/university that wasn't really scientific oriented. Presently i am doing an MSc in ...
2
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3answers
789 views

How to show Martingale property for sum of $S_k-E(S_k)$-summands where $S_k$ is a function of two RV's

EDIT: new formulation of the question (old version below). In a paper I found the statement that a certain sum $M_n =Y_1+\dotsb Y_n$ is a martingale, $Y_i=f (X_k, Z_k) - E ( f(X_k, Z_k) | X_k)$. (The ...
1
vote
1answer
63 views

Bound spectral radius of a certain matrix.

Consider a stochastic matrix $P$, i.e. real, non-negative, square, rows sum to one. Consider $\Xi = \text{diag}(\xi)$ to be a diagonal matrix with a principal left eigenvector $\xi$ of $P$ (i.e. ...
1
vote
3answers
518 views

Estimating the transition matrix given the stationary distribution

Let's say we are given a Markov chain for variable $X = [x_1, ..., x_n]$; also we are given a desired stationary distribution for this graph $P_\infty = [p_1, ..., p_n]^\top$. How can we design an ...
1
vote
1answer
495 views

Finding Markov chain transition matrix using mathematical induction

Let the transition matrix of a two-state Markov chain be $$P = \begin{bmatrix}p& 1-p\\ 1-p& p\end{bmatrix}$$ Questions: a. Use mathematical induction to find $P^n$. b. When n goes to ...
1
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0answers
158 views

a problem on DTMC

For a Markov chain $\{X_n, n\ge0\}$ with transition probabilities $P_{i,j}$, consider the conditional probability that $X_n = m$ given that the chain started at time $0$ in state $i$ and has not ...
4
votes
3answers
100 views

A recursive formula to approximate $e$. Prove or disprove.

Let the sequence $\{x_n, n=1,2,...\}$ be defined as follows: Let $x_2=x_1=1$ and for $n>2$ let $$x_{n+1}=x_n-\frac{1}{n}x_{n-1}.$$ This sequence, generated by the recursion above, tends to zero ...
4
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1answer
65 views

Find the Stationary Distribution of an infinite state Markov chain

A Markov Chain on states 0,1,..... has transition probabilities $P_{ij}=1/(i+2)$ for j=0,1,....,i,i+1. I'm supposed to find the stationary distribution. So do I take the limit as n goes to ...
4
votes
2answers
121 views

Markov and independent random variables

This is a part of an exercise in Durrett's probability book. Consider the Markov chain on $\{1,2,\cdots,N\}$ with $p_{ij}=1/(i-1)$ when $j<i, p_{11}=1$ and $p_{ij}=0$ otherwise. Suppose that we ...
3
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1answer
552 views

Proof about Steady-State distribution of a Markov chain

Consider $A$ as a matrix, that when normalized represents an finite-state time-homogeneous Markov chain $M$ with entries $0\leq p_{i,j}\leq 1$, where each row sums up to $1$. We can also assume that ...
3
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1answer
2k views

Finding the stationary distribution of a markov chain

I am asked to compute the stationary distribution of the markov chain with state space $E=\mathbb{N}_0$, $q_n >0$ for all $n \in \mathbb{N}_0$ and transition matrix below: \begin{bmatrix} q_0 ...
2
votes
1answer
80 views

Counterexample for $\| (\Phi^\top \Xi \Phi)^\dagger \Phi^\top \Xi P \Phi \|_2 \leq 1$

All matrices are real. Let $P$ be any stochastic matrix (i.e. square, non-negative, rows summing to one). Let $\Xi$ be a diagonal matrix containing on its diagonal any left eigenvector of $P$ ...
2
votes
1answer
48 views

Find conditions on the distribution on $X$, but what is meant by $X$?

Let $X, X_{n,k}$ for $k,n\in\mathbb{N}$ denote independent random variables with values in $\mathbb{N}_0$. Define $N_0:=1$ and for $n\in\mathbb{N}$ set $$ N_n:=\begin{cases}0, & \text{ ...
2
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1answer
2k views

Finding the steady state Markov chain?

I have drawn a certain Markov chain with a weird transition matrix. Here's the drawing: And here's the transition matrix: My problem is that I don't quite know how to calculate the steady state ...