Em Algorithm For Markov Chains Observed Via Gaussian Noise And Point Process Information

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EM Algorithm for Markov Chains Observed Via Gaussian Noise and Point Process Information

Author : Camilla Damian
Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis EM Algorithm for Markov Chains Observed Via Gaussian Noise and Point Process Information by : Camilla Damian

Download or read book EM Algorithm for Markov Chains Observed Via Gaussian Noise and Point Process Information written by Camilla Damian and published by . This book was released on 2017 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we study parameter estimation via the Expectation Maximization (EM) algorithm for a continuous-time hidden Markov model with diffusion and point process observation. Inference problems of this type arise for instance in credit risk modelling. A key step in the application of the EM algorithm is the derivation of finite-dimensional filters for the quantities that are needed in the E-step of the algorithm. In this context we obtain exact, unnormalized and robust filters, and we discuss their numerical implementation. Moreover, we propose several goodness-of-fit tests for hidden Markov models with Gaussian noise and point process observation. We run an extensive simulation study to test speed and accuracy of our methodology. The paper closes with an application to credit risk: we estimate the parameters of a hidden Markov model for credit quality where the observations consist of rating transitions and credit spreads for US corporations.

The EM Algorithm and Related Statistical Models

Author : Michiko Watanabe
Publisher : CRC Press
ISBN 13 : 9780203913055
Total Pages : 226 pages
Book Rating : 4.9/5 (13 download)

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Book Synopsis The EM Algorithm and Related Statistical Models by : Michiko Watanabe

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

Finite Markov Chains and Algorithmic Applications

Author : Olle Häggström
Publisher : Cambridge University Press
ISBN 13 : 9780521890014
Total Pages : 132 pages
Book Rating : 4.8/5 (9 download)

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Book Synopsis Finite Markov Chains and Algorithmic Applications by : Olle Häggström

Download or read book Finite Markov Chains and Algorithmic Applications written by Olle Häggström and published by Cambridge University Press. This book was released on 2002-05-30 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on a lecture course given at Chalmers University of Technology, this 2002 book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range of randomized algorithms with important applications in optimization and other problems in computing. Amongst the algorithms covered are the Markov chain Monte Carlo method, simulated annealing, and the recent Propp-Wilson algorithm. This book will appeal not only to mathematicians, but also to students of statistics and computer science. The subject matter is introduced in a clear and concise fashion and the numerous exercises included will help students to deepen their understanding.

Discrete-Time Markov Chains

Author : G. George Yin
Publisher : Springer Science & Business Media
ISBN 13 : 0387268715
Total Pages : 354 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Discrete-Time Markov Chains by : G. George Yin

Download or read book Discrete-Time Markov Chains written by G. George Yin and published by Springer Science & Business Media. This book was released on 2005-10-04 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on two-time-scale Markov chains in discrete time. Our motivation stems from existing and emerging applications in optimization and control of complex systems in manufacturing, wireless communication, and ?nancial engineering. Much of our e?ort in this book is devoted to designing system models arising from various applications, analyzing them via analytic and probabilistic techniques, and developing feasible compu- tionalschemes. Ourmainconcernistoreducetheinherentsystemcompl- ity. Although each of the applications has its own distinct characteristics, all of them are closely related through the modeling of uncertainty due to jump or switching random processes. Oneofthesalientfeaturesofthisbookistheuseofmulti-timescalesin Markovprocessesandtheirapplications. Intuitively,notallpartsorcom- nents of a large-scale system evolve at the same rate. Some of them change rapidly and others vary slowly. The di?erent rates of variations allow us to reduce complexity via decomposition and aggregation. It would be ideal if we could divide a large system into its smallest irreducible subsystems completely separable from one another and treat each subsystem indep- dently. However, this is often infeasible in reality due to various physical constraints and other considerations. Thus, we have to deal with situations in which the systems are only nearly decomposable in the sense that there are weak links among the irreducible subsystems, which dictate the oc- sional regime changes of the system. An e?ective way to treat such near decomposability is time-scale separation. That is, we set up the systems as if there were two time scales, fast vs. slow. xii Preface Followingthetime-scaleseparation,weusesingularperturbationmeth- ology to treat the underlying systems.

Theory and Use of the EM Algorithm

Author : Maya R. Gupta
Publisher : Now Publishers Inc
ISBN 13 : 1601984308
Total Pages : 87 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Theory and Use of the EM Algorithm by : Maya R. Gupta

Download or read book Theory and Use of the EM Algorithm written by Maya R. Gupta and published by Now Publishers Inc. This book was released on 2011 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the expectation-maximization (EM) algorithm and provides an intuitive and mathematically rigorous understanding of this method. Theory and Use of the EM Algorithm is designed to be useful to both the EM novice and the experienced EM user looking to better understand the method and its use.

Partially observed markov chains and point processes

Author : M. Rudemo
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (841 download)

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Book Synopsis Partially observed markov chains and point processes by : M. Rudemo

Download or read book Partially observed markov chains and point processes written by M. Rudemo and published by . This book was released on 1973 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computations with Markov Chains

Author : William J. Stewart
Publisher : Springer Science & Business Media
ISBN 13 : 1461522412
Total Pages : 605 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Computations with Markov Chains by : William J. Stewart

Download or read book Computations with Markov Chains written by William J. Stewart and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computations with Markov Chains presents the edited and reviewed proceedings of the Second International Workshop on the Numerical Solution of Markov Chains, held January 16--18, 1995, in Raleigh, North Carolina. New developments of particular interest include recent work on stability and conditioning, Krylov subspace-based methods for transient solutions, quadratic convergent procedures for matrix geometric problems, further analysis of the GTH algorithm, the arrival of stochastic automata networks at the forefront of modelling stratagems, and more. An authoritative overview of the field for applied probabilists, numerical analysts and systems modelers, including computer scientists and engineers.

MCMC from Scratch

Author : Masanori Hanada
Publisher : Springer Nature
ISBN 13 : 9811927154
Total Pages : 198 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis MCMC from Scratch by : Masanori Hanada

Download or read book MCMC from Scratch written by Masanori Hanada and published by Springer Nature. This book was released on 2022-10-20 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves. The content consists of six chapters. Following Chap. 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chap. 3 presents the general aspects of MCMC. Chap. 4 illustrates the essence of MCMC through the simple example of the Metropolis algorithm. In turn, Chap. 5 explains the HMC algorithm, Gibbs sampling algorithm and Metropolis-Hastings algorithm, discussing their pros, cons and pitfalls. Lastly, Chap. 6 presents several applications of MCMC. Including a wealth of examples and exercises with solutions, as well as sample codes and further math topics in the Appendix, this book offers a valuable asset for students and beginners in various fields.

Efficient Learning Machines

Author : Mariette Awad
Publisher : Apress
ISBN 13 : 1430259906
Total Pages : 263 pages
Book Rating : 4.4/5 (32 download)

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Book Synopsis Efficient Learning Machines by : Mariette Awad

Download or read book Efficient Learning Machines written by Mariette Awad and published by Apress. This book was released on 2015-04-27 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.

Partially Observed Markov Decision Processes

Author : Vikram Krishnamurthy
Publisher : Cambridge University Press
ISBN 13 : 1107134609
Total Pages : 491 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Partially Observed Markov Decision Processes by : Vikram Krishnamurthy

Download or read book Partially Observed Markov Decision Processes written by Vikram Krishnamurthy and published by Cambridge University Press. This book was released on 2016-03-21 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers formulation, algorithms, and structural results of partially observed Markov decision processes, whilst linking theory to real-world applications in controlled sensing. Computations are kept to a minimum, enabling students and researchers in engineering, operations research, and economics to understand the methods and determine the structure of their optimal solution.

Partially observed Markov chains and point processes

Author : Mats Rudemo
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.:/5 (487 download)

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Book Synopsis Partially observed Markov chains and point processes by : Mats Rudemo

Download or read book Partially observed Markov chains and point processes written by Mats Rudemo and published by . This book was released on 1973 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Numerical Methods for Structured Markov Chains

Author : Dario A. Bini
Publisher : Oxford University Press, USA
ISBN 13 : 0198527683
Total Pages : 340 pages
Book Rating : 4.1/5 (985 download)

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Book Synopsis Numerical Methods for Structured Markov Chains by : Dario A. Bini

Download or read book Numerical Methods for Structured Markov Chains written by Dario A. Bini and published by Oxford University Press, USA. This book was released on 2005-02-03 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intersecting two large research areas - numerical analysis and applied probability/queuing theory - this book is a self-contained introduction to the numerical solution of structured Markov chains, which have a wide applicability in queuing theory and stochastic modeling and include M/G/1 and GI/M/1-type Markov chain, quasi-birth-death processes, non-skip free queues and tree-like stochastic processes. Written for applied probabilists and numerical analysts, but accessible toengineers and scientists working on telecommunications and evaluation of computer systems performances, it provides a systematic treatment of the theory and algorithms for important families of structured Markov chains and a thorough overview of the current literature.The book, consisting of nine Chapters, is presented in three parts. Part 1 covers a basic description of the fundamental concepts related to Markov chains, a systematic treatment of the structure matrix tools, including finite Toeplitz matrices, displacement operators, FFT, and the infinite block Toeplitz matrices, their relationship with matrix power series and the fundamental problems of solving matrix equations and computing canonical factorizations. Part 2 deals with the description andanalysis of structure Markov chains and includes M/G/1, quasi-birth-death processes, non-skip-free queues and tree-like processes. Part 3 covers solution algorithms where new convergence and applicability results are proved. Each chapter ends with bibliographic notes for further reading, and the bookends with an appendix collecting the main general concepts and results used in the book, a list of the main annotations and algorithms used in the book, and an extensive index.

Continuous Parameter Markov Chains

Author : Kai Lai Chung
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Continuous Parameter Markov Chains by : Kai Lai Chung

Download or read book Continuous Parameter Markov Chains written by Kai Lai Chung and published by . This book was released on 1958 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modern Statistical Methods for Astronomy

Author : Eric D. Feigelson
Publisher : Cambridge University Press
ISBN 13 : 052176727X
Total Pages : 495 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Modern Statistical Methods for Astronomy by : Eric D. Feigelson

Download or read book Modern Statistical Methods for Astronomy written by Eric D. Feigelson and published by Cambridge University Press. This book was released on 2012-07-12 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Statistical Methods for Astronomy: With R Applications.

Approximate EM Algorithms for State Space Models with Markov Regime Changes

Author : Tianni Zhou
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (65 download)

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Book Synopsis Approximate EM Algorithms for State Space Models with Markov Regime Changes by : Tianni Zhou

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:

The Application of Hidden Markov Models in Speech Recognition

Author : Mark Gales
Publisher : Now Publishers Inc
ISBN 13 : 1601981201
Total Pages : 125 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis The Application of Hidden Markov Models in Speech Recognition by : Mark Gales

Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.

Advances in Neural Information Processing Systems 17

Author : Lawrence K. Saul
Publisher : MIT Press
ISBN 13 : 9780262195348
Total Pages : 1710 pages
Book Rating : 4.1/5 (953 download)

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Book Synopsis Advances in Neural Information Processing Systems 17 by : Lawrence K. Saul

Download or read book Advances in Neural Information Processing Systems 17 written by Lawrence K. Saul and published by MIT Press. This book was released on 2005 with total page 1710 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.