When this Markov chain is irreducible, it can be proved theoretically that the system will always return to its initial state, and also the expected time of return can be determined. This return time depends upon the stationary probability distribution, which is determined as the solution of an...
Expected return time and limits in discrete time Markov chain Ask Question Asked 6 years, 10 months ago Modified 6 years, 10 months ago Viewed 2k times This question shows research effort; it is useful and clear 3 Save this question. Show activity on this post. I have a d...
= mouse cat, mouse = step(cat, mouse) i += 1 end return i end function run() res = [game(cat_start, mouse_start) for i=1:10_000_000] return mean(res), std(res)/sqrt(length(res)) end μ,σ = run() println("Mean lifetime: $μ± $σ") Example output: Mean lifetime:...
This note investigates the use of extrapolations with certain iterative methods to accelerate the computation of the expected discounted return in a finite Markov chain. An easily administered algorithm for reordering the equations allows an attractive stopping rule to be used with Gauss-Seidel iteration...
The Markov chains were simulated using the Metropolis-within-Gibbs algorithm as described in the “Methods” section. Finally, for each set of the model parameters from the generated MCMC chain, we simulated the ETAS process forward in time using the well-established thinning algorithm42 and ...
a他这次患的流感比上次严重得多 He this time contracts flu previous time is much more serious than[translate] aIn addition to the probability of certain events, it is natural to analyze the average behavior of executions in a Markov chain. For instance, for a communication system where a sender...
When this Markov chain is irreducible, it can be proved theoretically that the system will always return to its initial state, and also the expected time of return can be determined. This return time depends upon the stationary probability distribution, which is determined as the solution of an...
The discounted return associated with a finite state Markov chain X sub 1, X sub 2... is given by g(X sub 1) + alpha 2g(X sub 3) + ..., where g(x) represents the immediate return from state x. Knowing the transition matrix of the chain, it is desired to compute the expected...
Markov chainsArticleIn the author's paper "Coupling and Mixing Times in Markov Chains" (Res. Lett. Inf. Math. Sci, 11, 1–22, 2007) it was shown that it is very difficult to find explicit expressions for the expected time to coupling in a general Markov chain. In this paper simple ...
Motivated in part by a problem in simulated tempering (a form of Markov chain Monte Carlo) we seek to minimise, in a suitable sense, the time it takes a (regular) diffusion with instantaneous reflection at 0 and 1 to travel from the origin to 1 and then return (the so-called commute ...