Results 11 to 20 of about 3,223,623 (259)
Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains [PDF]
, 2007 This paper is concerned with consistent nearest neighbor time series estimation for data generated by a Harris recurrent Markov chain. The goal is to validate nearest neighbor estimation in this general time series context, using simple and weak ...
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Markov chain Monte Carlo methods for state-space models with point process observations [PDF]
, 2012 This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan +2 more
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Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]
, 2014 Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Livingstone, Samuel +5 more
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CLTs and asymptotic variance of time-sampled Markov chains [PDF]
, 2011 For a Markov transition kernel P and a probability distribution μ on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel Pμ = Σkμ(k)Pk.
Łatuszyński, Krzysztof +3 more
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Advances in Mechanical Engineering, 2016 In order to solve the reliability assessment of braking system component of high-speed electric multiple units, this article, based on two-parameter exponential distribution, provides the maximum likelihood estimation and Bayes estimation under a type-I ...
Jianwei Yang +4 more
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A Kronecker Algebra Formulation for Markov Activity Networks with Phase-Type Distributions
Mathematics, 2021 The application of theoretical scheduling approaches to the real world quite often crashes into the need to cope with uncertain events and incomplete information. Stochastic scheduling approaches exploiting Markov models have been proposed for this class
Alessio Angius +2 more
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Time series segmentation with shifting means hidden markov models [PDF]
Nonlinear Processes in Geophysics, 2006 We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means ...
Ath. Kehagias, V. Fortin
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IEEE Access, 2018 Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang +3 more
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Estimating MS-BLGARCH Models Using Recursive Method
Pan-American Journal of Mathematics, 2023 In this paper a new class of models is proposed for modeling nonlinear and stationary time series. This new class of models is referred to as the Markov-switching bilinear GARCH (MS-BLGARCH) models.
Ahmed Ghezal, Imane Zemmouri
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A Bayesian model for binary Markov chains
International Journal of Mathematics and Mathematical Sciences, 2004 This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated.
Souad Assoudou, Belkheir Essebbar
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