2,829 research outputs found
Asymptotic Expansions for Moments of Hitting Times for Nonlinearly Perturbed Semi-Markov Processes
No full textIn Chapter 3, we introduce a model of perturbed semi-Markov processes, formulate basic perturbation conditions, describe a one-step time-space screening procedure of phase space reduction for perturbed semi-Markov processes, introduce hitting times, and prove an invariant property of them with respect to the procedure of phase space reduction. We, also, present algorithms for re-calculation of asymptotic expansions for transition characteristics of nonlinearly perturbed semi-Markov processes with reduced phase spaces and algorithms for sequential reduction of phase space for semi-Markov processes and construction of Laurent asymptotic expansions, without and with explicit upper bounds for remainders, for power moment of hitting times. © 2017, The Author(s).</p
Nonlinearly Perturbed Birth-Death-Type Semi-Markov Processes
No full textIn Chapter 5, we present asymptotic expansions for stationary and conditional quasi-stationary distributions of nonlinearly perturbed birth-death-type semi-Markov processes, which play an important role in many applications. In this case, the corresponding expansions can be given in a more explicit form. © 2017, The Author(s).</p
Time Series Modeling with Duration Dependent Markov-Switching Vector Autoregressions: MCMC Inference, Software and Applications
No full textDuration dependent Markov-switching VAR (DDMS-VAR) models are time series models with data generating process consisting in a mixture of two VAR processes, which switches according to a two-state Markov chain with transition probabilities depending on how long the process has been in a state. In the present paper I propose a MCMC-based methodology to carry out inference on the model's parameters and introduce DDMSVAR for Ox, a software written by the author for the analysis of time series by means of DDMS-VAR models. An application of the methodology to the U.S. business cycle concludes the article.Markov-switching, Business cycle, Gibbs sampling, Duration dependence, Vector autoregression
The cooperation and verification mechanism three years later : what has been done and what is yet to come
No full textDimitar MarkovElectronic ed.: Sofia ; Bonn : FES, 201
Markov closure for the Lundgren-Monin_Novikov hierarchy of velocity increments in Burgers turbulence
No full textA central, yet unsolved issue in the longstanding problem of hydrodynamic turbulence is the closure problem of turbulence, which is due to the nonlinear character of the Navier-Stokes equation. We formulate the closure problem for the many-increment probability distributions (PDF’s) in Burgers turbulence and introduce a new method for closing the hierarchy. To this end, we rely on the experimentally and numerically verified assumption in [1] that the turbulent cascade possesses a Markov property in scale down to the so-called Einstein-Markov length. The hierarchy is closed at the stage of the two-increment PDF corresponding to a three-point closure that allows for a description of intermittency effects, not captured by other closure approximations, i.e. Gaussian closures etc. The proposed closure also opens up a possible way to a perturbative treatment of the Navier-Stokes equation beyond the Einstein-Markov length in successively taking into account a larger and larger scale “history” of the system
Normal deviation and Poisson approximation of a security market by the geometric Markov renewal processes
No full textWe consider the geometric Markov renewal processes (GMRP) as a model for a security market. Normal deviations of the geometric Markov renewal processes for ergodic averaging and double averaging schemes are derived. We introduce Poisson averaging scheme for the geometric Markov renewal processes. European call option pricing formulas for GMRP are presented. [ABSTRACT FROM AUTHOR
Anglicized words and misspelled cognates in native language identification
No full textIn this paper, we present experiments that estimate the impact of specific lexical choices of people writing in a second language (L2). In particular, we look at misspelled words that indicate lexical uncertainty on the part of the author, and separate them into three categories: misspelled cognates, “L2-ed” (in our case, anglicized) words, and all other spelling errors. We test the assumption that such errors contain clues about the native language of an essay’s author through the task of native language identification. The results of the experiments show that the information brought by each of these categories is complementary. We also note that while the distribution of such features changes with the proficiency level of the writer, their contribution towards native language identification remains significant at all levels
Markov Modulated Process to Model Human Mobility
No full textWe introduce a Markov Modulated Process (MMP) to describe human mobility. We represent the mobility process as a time-varying graph, where a link specifies a connection between two nodes (humans) at any discrete time step. Each state of the Markov chain encodes a certain modification to the original graph. We show that our MMP model successfully captures the main features of a random mobility simulator, in which nodes moves in a square region. We apply our MMP model to human mobility, measured in a library.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Network Architectures and ServicesTransport and Plannin
On deltamodulators for Gauss-Markov-processes : a normal approximation
No full textThe author studies the properties of deltamodulators for signals consisting of sample paths of a time-continuous Gauss-Markov-process (source). The deltamodulator output is a (square integrable) functional of the source path, which implies a representation (decomposition) in terms of a stochastic integral. From this representation one finds the conditional expectation and the variance of any decoded variable. Using the properties of such deltamodulators, it becomes possible to provide a normal approximation for the decoded output. In addition, various types of errors, which are known as pointwise approximation error, pointwise prediction error, pointwise predicted error and overload slope error, are described.</p
Derivations and KMS-Symmetric Quantum Markov Semigroups
No full textWe prove that the generator of the implementation of a KMS-symmetric
quantum Markov semigroup can be expressed as the square of a derivation with
values in a Hilbert bimodule, extending earlier results by Cipriani and
Sauvageot for tracially symmetric semigroups and the second-named author for
GNS-symmetric semigroups. This result hinges on the introduction of a new
completely positive map on the algebra of bounded operators on the GNS Hilbert
space. This transformation maps symmetric Markov operators to symmetric Markov
operators and is essential to obtain the required inner product on the Hilbert
bimodule.Comment: 35 pages, implemented small changes based on reviewers comments.
Accepted in Communications in Mathematical Physic
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