Limiting Distributions in Markov Chains
ثبت نشده
چکیده
One of the principal questions involving Markov chains is what are the long-time (asymptotic) properties of the chain? Before we can formulate the question precisely, we need to introduce some ideas. Suppose we have a Markov chain {Xn}n∈N on a finite or countable state space S with transition probabilities Pi,j = P (Xn+1 = j | Xn = i), i, j ∈ S. We let N denote the number of elements in S (note that N =∞ is allowed).
منابع مشابه
Approximations of Quasistationary Distributions for Markov Chains
We consider a simple and widely used method for evaluating quasistationary distributions of continuous time Markov chains. The infinite state space is replaced by a large, but finite approximation, which is used to evaluate a candidate distribution. We give some conditions under which the method works, and describe some important pitfalls. μ-subinvariant measures; conditioned processes; limitin...
متن کاملAchieving limiting distributions for Markov chains using back buttons
As a simple model for browsing the World Wide Web, we consider Markov chains with the option of moving “back” to the previous state. We develop an algorithm which uses back buttons to achieve essentially any limiting distribution on the state space. This corresponds to spending the desired total fraction of time at each web page. On finite state spaces, our algorithm always succeeds. On infinit...
متن کاملEstimatio : : of Ihe Transition Distributions of a Markov Renewal Process
The present paper is concerned with the eetlmatlon of the transition distributions of a Markov renewal process with finitely many states, which extends and unifies nome aspects of the results in the special cases of discrete and continuous parameter Markov chains. A natural estimator of the transition distribution." is defined and shown to be consistent. Limiting distributions of this estimator...
متن کاملSequentially Interacting Markov Chain Monte Carlo Methods
We introduce a novel methodology for sampling from a sequence of probability distributions of increasing dimension and estimating their normalizing constants. These problems are usually addressed using Sequential Monte Carlo (SMC) methods. The alternative Sequentially Interacting Markov Chain Monte Carlo (SIMCMC) scheme proposed here works by generating interacting non-Markovian sequences which...
متن کاملQuasi-Stationary Distributions for Reducible Absorbing Markov Chains in Discrete Time
We consider discrete-time Markov chains with one coffin state and a finite set S of transient states, and are interested in the limiting behaviour of such a chain as time n tends to infinity, conditional on survival up to n. It is known that, when S is irreducible, the limiting conditional distribution of the chain equals the (unique) quasi-stationary distribution of the chain, while the latter...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014