Results 71 to 80 of about 111 (110)
Ruelle's Transfer Operator for Random Subshifts of Finite Type
, 1995 We consider a Ruelle-Perron-Frobenius type of selection procedure for probability measures that are invariant under random subshifts of finite type. In particular we prove that for a class of random functions this method leads to a unique probability ...
Volker Matthias Gundlach +1 more
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Reliable uncertainties of tests and surveys – a data-driven approach [PDF]
MSC Classification 60J10, 91Exx, 91E45, 05A18.Supplementary material are available online at: https://www.metrology-journal.org/10.1051/ijmqe/2023018/olm .
Wang, K +2 more
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Embeddability of centrosymmetric matrices capturing the double-helix structure in natural and synthetic DNA. [PDF]
J Math Biol, 2023 Ardiyansyah M +2 more
europepmc +1 more source
, 1995 We introduce random homoclinic points and orbits for random dynamical systems with hyperbolic stationary orbits and investigate their meaning for irregular behaviour in form of a stochastic version of the Birkhoff-Smale Theorem.
Volker Matthias Gundlach
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Staircase patterns in words: subsequences, subwords, and separation number. [PDF]
Eur J Comb, 2020 Mansour T, Rastegar R, Roitershtein A.
europepmc +1 more source
Extension of Fill's perfect rejection sampling algorithm to general chains
, 1999 By developing and applying a broad framework for rejection sampling using auxiliary randomness, we provide an extension of the perfect sampling algorithm of Fill (1998) to general chains on quite general state spaces, and describe how use of bounding ...
Motoya Machida +3 more
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General Conditions for Bounded Relative Error in Simulations of Highly Reliable Markovian Systems
, 1996 We establish a necessary condition for any importance sampling scheme to give bounded relative error when estimating a performance measure of a highly reliable Markovian system. Also, a class of importance sampling methods is defined for which we prove a
Marvin K. Nakayama, Marvin Nakayama
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The consistency of the BIC Markov order estimator.
, 2007 . The Bayesian Information Criterion (BIC) estimates the order of a Markov chain (with finite alphabet A) from observation of a sample path x 1 ; x 2 ; : : : ; x n , as that value k = k that minimizes the sum of the negative logarithm of the k-th order
Imre Csiszár, Paul C. Shields
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Computable Bounds For Polynomial Ergodicity
, 2002 This paper discusses quantitative bounds on the convergence rates of Markov chains, under conditions implying polynomial convergence rates. This paper extends an earlier work by Roberts and Tweedie [17], which provides quantitative bounds for the total ...
G. Fort, E. Moulines
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Random motions, classes of ergodic Markov chains and beta distributions
We consider classes of discrete time Markov chains with continuous state space, the interval (0, 1). These chains arise as stochastic models of phenomena in areas such as population theory, motion of particles in a random environment, etc. We exploit the
Stoyanov J; Pirinsky C
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