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Author : Tianni Zhou
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (65 download)
Download or read book Approximate EM Algorithms for State Space Models with Markov Regime Changes written by Tianni Zhou and published by . This book was released on 2002 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Chang-Jin Kim
Publisher : Mit Press
ISBN 13 : 9780262112383
Total Pages : 297 pages
Book Rating : 4.1/5 (123 download)
Download or read book State-space Models with Regime Switching written by Chang-Jin Kim and published by Mit Press. This book was released on 1999 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
Author : Chang-Jin Kim
Publisher : MIT Press
ISBN 13 : 0262535505
Total Pages : 312 pages
Book Rating : 4.2/5 (625 download)
Download or read book State-Space Models with Regime Switching written by Chang-Jin Kim and published by MIT Press. This book was released on 2017-11-03 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data. The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
Author : Robert H. Shumway
Publisher :
ISBN 13 : 9781475732627
Total Pages : 568 pages
Book Rating : 4.7/5 (326 download)
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Shuheng Zheng
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (893 download)
Download or read book Stochastic Approximation Algorithms in the Estimation of Quasi-Stationary Distribution of Finite and General State Space Markov Chains written by Shuheng Zheng and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: It is discovered that the rate of convergence is only fast when a certain restrictive eigenvalue condition is satisfied. Using the tool of iterate averaging, the algorithm can be modified and we can eliminate the eigenvalue condition. The thesis then moves onto the general state space discrete-time Markov chain setting. In this setting, the stochastic approximation framework does not have a strong theory in the current literature, so several of the convergence results have to be adapted because the iterates of our algorithm are measure-valued The chapter formulates the quasi-stationary estimation algorithm in this setting. Then, we extend the ODE method of [#kushner2003stochastic] and proves the consistency of algorithm. Through the proof, several non-restrictive conditions required for convergence of the algorithm are discovered. Finally, the thesis tests the algorithm by running some numerical experiments. The examples are designed to test the algorithm in various edge cases. The algorithm is also empirically compared against the Fleming-Viot method.
Author : Anna Gambin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)
Download or read book Combinatorial Methods in Approximation Algorithms for Markov Chains with Large State Space written by Anna Gambin and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michiko Watanabe
Publisher : CRC Press
ISBN 13 : 9780203913055
Total Pages : 226 pages
Book Rating : 4.9/5 (13 download)
Download or read book The EM Algorithm and Related Statistical Models written by Michiko Watanabe and published by CRC Press. This book was released on 2003-10-15 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including sta
Author : Andrew M. Fraser
Publisher : SIAM
ISBN 13 : 0898717744
Total Pages : 142 pages
Book Rating : 4.8/5 (987 download)
Download or read book Hidden Markov Models and Dynamical Systems written by Andrew M. Fraser and published by SIAM. This book was released on 2008-01-01 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides an introduction to hidden Markov models (HMMs) for the dynamical systems community. It is a valuable text for third or fourth year undergraduates studying engineering, mathematics, or science that includes work in probability, linear algebra and differential equations. The book presents algorithms for using HMMs, and it explains the derivation of those algorithms. It presents Kalman filtering as the extension to a continuous state space of a basic HMM algorithm. The book concludes with an application to biomedical signals. This text is distinctive for providing essential introductory material as well as presenting enough of the theory behind the basic algorithms so that the reader can use it as a guide to developing their own variants.
Author : Hyeong Soo Chang
Publisher : Springer Science & Business Media
ISBN 13 : 1447150228
Total Pages : 241 pages
Book Rating : 4.4/5 (471 download)
Download or read book Simulation-Based Algorithms for Markov Decision Processes written by Hyeong Soo Chang and published by Springer Science & Business Media. This book was released on 2013-02-26 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable. In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function. Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search. This substantially enlarged new edition reflects the latest developments in novel algorithms and their underpinning theories, and presents an updated account of the topics that have emerged since the publication of the first edition. Includes: innovative material on MDPs, both in constrained settings and with uncertain transition properties; game-theoretic method for solving MDPs; theories for developing roll-out based algorithms; and details of approximation stochastic annealing, a population-based on-line simulation-based algorithm. The self-contained approach of this book will appeal not only to researchers in MDPs, stochastic modeling, and control, and simulation but will be a valuable source of tuition and reference for students of control and operations research.
Author :
Publisher :
ISBN 13 :
Total Pages : 850 pages
Book Rating : 4.F/5 ( download)
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Leland Farmer
Publisher :
ISBN 13 :
Total Pages : 27 pages
Book Rating : 4.:/5 (13 download)
Download or read book Markov-Chain Approximation and Estimation of Nonlinear, Non-Gaussian State Space Models written by Leland Farmer and published by . This book was released on 2014 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: I develop a new method for approximating and estimating nonlinear, non-Gaussian state space models. I show that any such model can be well approximated by a discrete-state Markov process and estimated using techniques developed in Hamilton (1989). Through Monte Carlo simulations, I demonstrate that my method outperforms popular existing methods both in terms of accuracy and computational efficiency for empirically relevant sample sizes. This finding has important implications for the estimation of nonlinear dynamic economic models, many of which are computationally intractable using exisiting methods. I illustrate an empirical application of my method by re-estimating the Wu and Xia shadow rate term structure model. When I calculate the shadow rate using the parameter estimates from my proposed filter, I find that it was as much as 2.2 percentange points lower in July 2012 than previous estimates imply.
Author : Olivier Cappé
Publisher : Springer Science & Business Media
ISBN 13 : 0387289828
Total Pages : 656 pages
Book Rating : 4.3/5 (872 download)
Download or read book Inference in Hidden Markov Models written by Olivier Cappé and published by Springer Science & Business Media. This book was released on 2006-04-12 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.
Author : Yoosoon Chang
Publisher :
ISBN 13 :
Total Pages : 49 pages
Book Rating : 4.:/5 (13 download)
Download or read book Origins of Monetary Policy Shifts written by Yoosoon Chang and published by . This book was released on 2019 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article studies the estimation of state space models whose parameters are switching endogenously between two regimes, depending on whether an autoregressive latent factor crosses some threshold level. Endogeneity stems from the sustained impacts of transition innovations on the latent factor, absent from which our model reduces to one with exogenous Markov switching. Due to the exible form of state space representation, this class of models is vastly broad, including classical regression models and the popular dynamic stochastic general equilibrium (DSGE) models as special cases. We develop a computationally efficient filtering algorithm to estimate the nonlinear model. Calculations are greatly simplified by appropriate augmentation of the transition equation and exploiting the conditionally linear and Gaussian structure. The algorithm is shown to be accurate in approximating both the likelihood function and filtered state variables. We also apply the filter to estimate a small-scale DSGE model with threshold-type switching in monetary policy rule, and find apparent empirical evidence of endogeneity in the U.S. monetary policy shifts. Overall, our approach provides a greater scope for understanding the complex interaction between regime switching and measured economic behavior.
Author : Csaba Grossi
Publisher : Springer Nature
ISBN 13 : 3031015517
Total Pages : 89 pages
Book Rating : 4.0/5 (31 download)
Download or read book Algorithms for Reinforcement Learning written by Csaba Grossi and published by Springer Nature. This book was released on 2022-05-31 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration
Author : Robert A. Meyers
Publisher : Springer Science & Business Media
ISBN 13 : 1441977007
Total Pages : 919 pages
Book Rating : 4.4/5 (419 download)
Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Author : James D. Hamilton
Publisher : Springer Science & Business Media
ISBN 13 : 3642511821
Total Pages : 267 pages
Book Rating : 4.6/5 (425 download)
Download or read book Advances in Markov-Switching Models written by James D. Hamilton and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of state-of-the-art papers on the properties of business cycles and financial analysis. The individual contributions cover new advances in Markov-switching models with applications to business cycle research and finance. The introduction surveys the existing methods and new results of the last decade. Individual chapters study features of the U. S. and European business cycles with particular focus on the role of monetary policy, oil shocks and co movements among key variables. The short-run versus long-run consequences of an economic recession are also discussed. Another area that is featured is an extensive analysis of currency crises and the possibility of bubbles or fads in stock prices. A concluding chapter offers useful new results on testing for this kind of regime-switching behaviour. Overall, the book provides a state-of-the-art over view of new directions in methods and results for estimation and inference based on the use of Markov-switching time-series analysis. A special feature of the book is that it includes an illustration of a wide range of applications based on a common methodology. It is expected that the theme of the book will be of particular interest to the macroeconomics readers as well as econometrics professionals, scholars and graduate students. We wish to express our gratitude to the authors for their strong contributions and the reviewers for their assistance and careful attention to detail in their reports.
Author : Vladimir Anisimov
Publisher : John Wiley & Sons
ISBN 13 : 1118623487
Total Pages : 268 pages
Book Rating : 4.1/5 (186 download)
Download or read book Switching Processes in Queueing Models written by Vladimir Anisimov and published by John Wiley & Sons. This book was released on 2013-03-01 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Switching processes, invented by the author in 1977, is the main tool used in the investigation of traffic problems from automotive to telecommunications. The title provides a new approach to low traffic problems based on the analysis of flows of rare events and queuing models. In the case of fast switching, averaging principle and diffusion approximation results are proved and applied to the investigation of transient phenomena for wide classes of overloading queuing networks. The book is devoted to developing the asymptotic theory for the class of switching queuing models which covers models in a Markov or semi-Markov environment, models under the influence of flows of external or internal perturbations, unreliable and hierarchic networks, etc.
