Search results for "markov chain"
showing 10 items of 288 documents
ON HIGH-SKILL AND LOW-SKILL EQUILIBRIA: A MARKOV CHAIN APPROACH
2006
In this paper we propose to study the dynamics of human capital accumulation by means of a Markov chain. We identify the conditions for the emergence of ergodic and nonergodic dynamics, and relate them to various characteristics of an economic system. The model may generate high-skill and low-skill equilibria as well as intermediate situations. Policy implications are also discussed.
Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes
2015
In the present study, we introduce novel 3D protein descriptors based on the bilinear algebraic form in the ℝn space on the coulombic matrix. For the calculation of these descriptors, macromolecular vectors belonging to ℝn space, whose components represent certain amino acid side-chain properties, were used as weighting schemes. Generalization approaches for the calculation of inter-amino acidic residue spatial distances based on Minkowski metrics are proposed. The simple- and double-stochastic schemes were defined as approaches to normalize the coulombic matrix. The local-fragment indices for both amino acid-types and amino acid-groups are presented in order to permit characterizing fragme…
Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo
2020
We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelisation and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the sug…
k-out-of-n systems: an exact formula for the stationary availability and multi-objective configuration design based on mathematical programming and T…
2018
[EN] Reliability and availability analyses are recognized as essential for guiding decision makers in the implementation of actions addressed to improve the technical and economical performance of complex systems. For industrial systems with reparable components, the most interesting parameter used to drive maintenance is the stationary availability. In this regard, the present paper proposes an exact formula for computing the system stationary availability of a k-out-of-n system. Such a formula is proved to be in agreement with the fundamental theorem of Markov chains. Then, a multi-objective mathematical model is formulated for choosing the optimal system configuration design. The Pareto …
Poisson convergence on continuous time branching random walks and multistage carcinogenesis.
1982
A theorem for Poisson convergence on realizations of two-dimensional Branching Random Walks with an underlying continuous time Markov Branching Process is proved. This result can be used to gain an approximation for the number of cells having sustained a certain deficiency after a long time in multistage carcinogenesis.
Forecasting correlated time series with exponential smoothing models
2011
Abstract This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection crite…
Improving the Performance Metric of Wireless Sensor Networks with Clustering Markov Chain Model and Multilevel Fusion
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/783543 Open access The paper proposes a performance metric evaluation for a distributed detection wireless sensor network with respect to IEEE 802.15.4 standard. A distributed detection scheme is considered with presence of the fusion node and organized sensors into the clustering and non-clustering networks. Sensors are distributed in clusters uniformly and nonuniformly and network has multilevel fusion centers. Fusion centers act as heads of clusters for decision making based on majority-like received signal strength (RSS) with comparis…
Updated determination of the solar neutrino fluxes from solar neutrino data
2016
Journal of High Energy Physics 2016.3 (2016): 132 reproduced by permission of Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Jet evolution in a dense medium: event-by-event fluctuations and multi-particle correlations
2017
International audience; We study the gluon distribution produced via successive medium-induced branchings by an energetic jet propagating through a weakly-coupled quark-gluon plasma. We show that under suitable approximations, the jet evolution is a Markovian stochastic process, which is exactly solvable. For this process, we construct exact analytic solutions for all the n-point correlation functions describing the gluon distribution in the space of energy [M. A. Escobedo, E. Iancu, Event-by-event fluctuations in the medium-induced jet evolution, JHEP 05 (2016) 008. arXiv: arXiv:1601.03629 , doi: http://dx.doi.org/10.1007/JHEP05(2016)008 , M. A. Escobedo, E. Iancu, Multi-particle correlati…
A novel method based on augmented Markov vector process for the time-variant extreme value distribution of stochastic dynamical systems enforced by P…
2020
Abstract The probability density function (PDF) of the time-variant extreme value process for structural responses is of great importance. Poisson white noise excitation occurs widely in practical engineering problems. The extreme value distribution of the response of systems excited by Poisson white noise processes is still not yet readily available. For this purpose, in the present paper, a novel method based on the augmented Markov vector process for the PDF of the time-variant extreme value process for a Poisson white noise driven dynamical system is proposed. Specifically, the augmented Markov vector (AMV) process is constructed by combining the extreme value process and its underlying…