Academic literature on the topic 'Infinitesimal generator matrix'

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Journal articles on the topic "Infinitesimal generator matrix"

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Borges, Carlos F., and Craig S. Peters. "Computing approximate stationary distributions for discrete Markov processes with banded infinitesimal generators." Journal of Applied Probability 36, no. 04 (1999): 1086–100. http://dx.doi.org/10.1017/s0021900200017885.

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We develop an algorithm for computing approximations to the stationary distribution of a discrete birth-and-death process, provided that the infinitesimal generator is a banded matrix. We begin by computing stationary distributions for processes whose infinitesimal generators are Hessenberg. Our derivation in this special case is different from the classical case but it leads to the same result. We then show how to extend these ideas to processes where the infinitesimal generator is banded (or half-banded) and to quasi-birth–death processes. Finally, we give an example of the application of th
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Borges, Carlos F., and Craig S. Peters. "Computing approximate stationary distributions for discrete Markov processes with banded infinitesimal generators." Journal of Applied Probability 36, no. 4 (1999): 1086–100. http://dx.doi.org/10.1239/jap/1032374757.

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We develop an algorithm for computing approximations to the stationary distribution of a discrete birth-and-death process, provided that the infinitesimal generator is a banded matrix. We begin by computing stationary distributions for processes whose infinitesimal generators are Hessenberg. Our derivation in this special case is different from the classical case but it leads to the same result. We then show how to extend these ideas to processes where the infinitesimal generator is banded (or half-banded) and to quasi-birth–death processes. Finally, we give an example of the application of th
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Uetake, Yoichi. "The Lax–Phillips infinitesimal generator and the scattering matrix for automorphic functions." Annales Polonici Mathematici 92, no. 2 (2007): 99–122. http://dx.doi.org/10.4064/ap92-2-1.

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Brown, Mark, and Yi-Shi Shao. "Identifying Coefficients in the Spectral Representation for First Passage Time Distributions." Probability in the Engineering and Informational Sciences 1, no. 1 (1987): 69–74. http://dx.doi.org/10.1017/s0269964800000309.

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The spectral approach to first passage time distributions for Markov processes requires knowledge of the eigenvalues and eigenvectors of the infinitesimal generator matrix. We demonstrate that in many cases knowledge of the eigenvalues alone is sufficient to compute the first passage time distribution.
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Carette, Philippe. "Modelling hierarchical systems by a continuous-time homogeneous Markov chain using two-wave panel data." Journal of Applied Probability 36, no. 03 (1999): 644–53. http://dx.doi.org/10.1017/s0021900200017460.

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An open hierarchical (manpower) system divided into a totally ordered set of k grades is discussed. The transitions occur only from one grade to the next or to an additional (k+1)th grade representing the external environment of the system. The model used to describe the dynamics of the system is a continuous-time homogeneous Markov chain with k+1 states and infinitesimal generator R = (r ij ) satisfying r ij = 0 if i > j or i + 1 < j ≤ k (i, j = 1,…,k+1), the transition matrix P between times 0 and 1 being P = exp R . In this paper, two-wave panel data about the hierarchical sys
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Carette, Philippe. "Modelling hierarchical systems by a continuous-time homogeneous Markov chain using two-wave panel data." Journal of Applied Probability 36, no. 3 (1999): 644–53. http://dx.doi.org/10.1239/jap/1032374623.

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An open hierarchical (manpower) system divided into a totally ordered set of k grades is discussed. The transitions occur only from one grade to the next or to an additional (k+1)th grade representing the external environment of the system. The model used to describe the dynamics of the system is a continuous-time homogeneous Markov chain with k+1 states and infinitesimal generator R = (rij) satisfying rij = 0 if i > j or i + 1 < j ≤ k (i, j = 1,…,k+1), the transition matrix P between times 0 and 1 being P = expR. In this paper, two-wave panel data about the hierarchical system are consi
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Dayar, TuǦrul, and M. Can Orhan. "Kronecker-Based Infinite Level-Dependent QBD Processes." Journal of Applied Probability 49, no. 04 (2012): 1166–87. http://dx.doi.org/10.1017/s002190020001295x.

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Markovian systems with multiple interacting subsystems under the influence of a control unit are considered. The state spaces of the subsystems are countably infinite, whereas that of the control unit is finite. A recent infinite level-dependent quasi-birth-and-death model for such systems is extended by facilitating the automatic representation and generation of the nonzero blocks in its underlying infinitesimal generator matrix with sums of Kronecker products. Experiments are performed on systems of stochastic chemical kinetics having two or more countably infinite state space subsystems. Re
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Dayar, TuǦrul, and M. Can Orhan. "Kronecker-Based Infinite Level-Dependent QBD Processes." Journal of Applied Probability 49, no. 4 (2012): 1166–87. http://dx.doi.org/10.1239/jap/1354716665.

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Markovian systems with multiple interacting subsystems under the influence of a control unit are considered. The state spaces of the subsystems are countably infinite, whereas that of the control unit is finite. A recent infinite level-dependent quasi-birth-and-death model for such systems is extended by facilitating the automatic representation and generation of the nonzero blocks in its underlying infinitesimal generator matrix with sums of Kronecker products. Experiments are performed on systems of stochastic chemical kinetics having two or more countably infinite state space subsystems. Re
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PARK, Y., K. M. SHAW, H. J. CHIEL, and P. J. THOMAS. "The infinitesimal phase response curves of oscillators in piecewise smooth dynamical systems." European Journal of Applied Mathematics 29, no. 5 (2018): 905–40. http://dx.doi.org/10.1017/s0956792518000128.

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The asymptotic phase θ of an initial point x in the stable manifold of a limit cycle (LC) identifies the phase of the point on the LC to which the flow φt(x) converges as t → ∞. The infinitesimal phase response curve (iPRC) quantifies the change in timing due to a small perturbation of a LC trajectory. For a stable LC in a smooth dynamical system, the iPRC is the gradient ∇x(θ) of the phase function, which can be obtained via the adjoint of the variational equation. For systems with discontinuous dynamics, the standard approach to obtaining the iPRC fails. We derive a formula for the iPRCs of
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Fackeldey, Konstantin, Amir Niknejad, and Marcus Weber. "Finding metastabilities in reversible Markov chains based on incomplete sampling." Special Matrices 5, no. 1 (2017): 73–81. http://dx.doi.org/10.1515/spma-2017-0006.

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Abstract In order to fully characterize the state-transition behaviour of finite Markov chains one needs to provide the corresponding transition matrix P. In many applications such as molecular simulation and drug design, the entries of the transition matrix P are estimated by generating realizations of the Markov chain and determining the one-step conditional probability Pij for a transition from one state i to state j. This sampling can be computational very demanding. Therefore, it is a good idea to reduce the sampling effort. The main purpose of this paper is to design a sampling strategy,
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Dissertations / Theses on the topic "Infinitesimal generator matrix"

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Ibrahim, Basil. "Queueing Analysis of a Priority-based Claim Processing System." Thesis, 2009. http://hdl.handle.net/10012/4796.

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We propose a situation in which a single employee is responsible for processing incoming claims to an insurance company that can be classified as being one of two possible types. More specifically, we consider a priority-based system having separate buffers to store high priority and low priority incoming claims. We construct a mathematical model and perform queueing analysis to evaluate the performance of this priority-based system, which incorporates the possibility of claims being redistributed, lost, or prematurely processed.
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Books on the topic "Infinitesimal generator matrix"

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Walsh, Bruce, and Michael Lynch. Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0019.

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When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and their Bayesian extensions. In this setting, REML can be used to estimate genetic variances and BLUP can be used to estimate the mean breeding value in any given generation. The latter allows for genetic trends to be separated from environmental trends without the need for a control population. Under the infinitesimal model setting (wherein selection-induced allele-frequency changes are small during
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Book chapters on the topic "Infinitesimal generator matrix"

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"Infinitesimal Generator Matrix." In Encyclopedia of Operations Research and Management Science. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_201008.

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Conference papers on the topic "Infinitesimal generator matrix"

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Zussman, Eyal, Moshe Shoham, and Ehud Lenz. "Kinematic Evaluation of Robots for Assembly Tasks." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0180.

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Abstract An automatic assembly planning program should be able to analyze the assembly kinematic constraints, generate possible motions and select the appropriate assembly machines. This paper develops an approach for evaluating a robot for assembly tasks and planning its motions. The kinematical characteristics of both the robot and the assembly tasks are described by infinitesimal screws. The possible motions of the assembled parts are represented by convex cone of screws derived from the geometrical constraints. The robot’s possible motions are represented by the Jacobian cone, which is a m
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