Explicit Duration Markov Switching Models

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Explicit-duration Markov Switching Models

Author : Silvia Chiappa
Publisher : Unknown
Page : 83 pages
File Size : 52,6 Mb
Release : 2014
Category : Markov processes
ISBN : 1601988311

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Explicit-duration Markov Switching Models by Silvia Chiappa Pdf

Markov switching models (MSMs) are probabilistic models that employ multiple sets of parameters to describe different dynamic regimes that a time series may exhibit at different periods of time. The switching mechanism between regimes is controlled by unobserved random variables that form a first-order Markov chain. Explicit-duration MSMs contain additional variables that explicitly model the distribution of time spent in each regime. This allows to define duration distributions of any form, but also to impose complex dependence between the observations and to reset the dynamics to initial conditions. Models that focus on the first two properties are most commonly known as hidden semi-Markov models or segment models, whilst models that focus on the third property are most commonly known as changepoint models or reset models. In this monograph, we provide a description of explicit-duration modelling by categorizing the different approaches into three groups, which differ in encoding in the explicit-duration variables different information about regime change/reset boundaries. The approaches are described using the formalism of graphical models, which allows to graphically represent and assess statistical dependence and therefore to easily describe the structure of complex models and derive inference routines. The presentation is intended to be pedagogical, focusing on providing a characterization of the three groups in terms of model structure constraints and inference properties. The monograph is supplemented with a software package that contains most of the models and examples described. The material presented should be useful to both researchers wishing to learn about these models and researchers wishing to develop them further.

Explicit-Duration Markov Switching Models

Author : Silvia Chiappa
Publisher : Now Pub
Page : 102 pages
File Size : 42,7 Mb
Release : 2014-12-19
Category : Computers
ISBN : 1601988303

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Explicit-Duration Markov Switching Models by Silvia Chiappa Pdf

Provides a simple and clear description of explicit duration modeling. The presentation focuses on making distinctions that help structure the space of models and in laying out inference and learning in a clear way. It is an ideal reference for students and researchers wishing to learn about these models and those looking to develop them further.

Neural Information Processing

Author : Biao Luo,Long Cheng,Zheng-Guang Wu,Hongyi Li,Chaojie Li
Publisher : Springer Nature
Page : 590 pages
File Size : 48,9 Mb
Release : 2023-11-25
Category : Computers
ISBN : 9789819981380

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Neural Information Processing by Biao Luo,Long Cheng,Zheng-Guang Wu,Hongyi Li,Chaojie Li Pdf

The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

Analytical Derivatives for Markov Switching Models

Author : Jeff Gable,Simon Van Norden,Robert Vigfusson
Publisher : Unknown
Page : 24 pages
File Size : 43,5 Mb
Release : 1995
Category : Markov processes
ISBN : 0662236858

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Analytical Derivatives for Markov Switching Models by Jeff Gable,Simon Van Norden,Robert Vigfusson Pdf

Advanced State Space Methods for Neural and Clinical Data

Author : Zhe Chen
Publisher : Cambridge University Press
Page : 397 pages
File Size : 49,5 Mb
Release : 2015-10-15
Category : Computers
ISBN : 9781107079199

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Advanced State Space Methods for Neural and Clinical Data by Zhe Chen Pdf

An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.

Finite Mixture and Markov Switching Models

Author : Sylvia Frühwirth-Schnatter
Publisher : Springer Science & Business Media
Page : 506 pages
File Size : 44,9 Mb
Release : 2006-11-24
Category : Mathematics
ISBN : 9780387357683

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Finite Mixture and Markov Switching Models by Sylvia Frühwirth-Schnatter Pdf

The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.

Handbook of Mixture Analysis

Author : Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert
Publisher : CRC Press
Page : 388 pages
File Size : 49,9 Mb
Release : 2019-01-04
Category : Computers
ISBN : 9780429508868

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Handbook of Mixture Analysis by Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert Pdf

Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Hidden Markov and Other Models for Discrete- valued Time Series

Author : Iain L. MacDonald,Walter Zucchini
Publisher : CRC Press
Page : 256 pages
File Size : 52,5 Mb
Release : 1997-01-01
Category : Mathematics
ISBN : 0412558505

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Hidden Markov and Other Models for Discrete- valued Time Series by Iain L. MacDonald,Walter Zucchini Pdf

Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been developed which are specifically designed for the analysis of discrete-valued time series. Hidden Markov and Other Models for Discrete-Valued Time Series introduces a new, versatile, and computationally tractable class of models, the "hidden Markov" models. It presents a detailed account of these models, then applies them to data from a wide range of diverse subject areas, including medicine, climatology, and geophysics. This book will be invaluable to researchers and postgraduate and senior undergraduate students in statistics. Researchers and applied statisticians who analyze time series data in medicine, animal behavior, hydrology, and sociology will also find this information useful.

Hidden Semi-Markov Models

Author : Shun-Zheng Yu
Publisher : Morgan Kaufmann
Page : 208 pages
File Size : 51,6 Mb
Release : 2015-10-22
Category : Computers
ISBN : 9780128027714

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Hidden Semi-Markov Models by Shun-Zheng Yu Pdf

Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. Hidden Semi-Markov Models: Theory, Algorithms and Applications provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science. Discusses the latest developments and emerging topics in the field of HSMMs Includes a description of applications in various areas including, Human Activity Recognition, Handwriting Recognition, Network Traffic Characterization and Anomaly Detection, and Functional MRI Brain Mapping. Shows how to master the basic techniques needed for using HSMMs and how to apply them.

Nonlinear Financial Econometrics: Markov Switching Models, Persistence and Nonlinear Cointegration

Author : Greg N. Gregoriou,Razvan Pascalau
Publisher : Springer
Page : 196 pages
File Size : 47,5 Mb
Release : 2010-12-08
Category : Business & Economics
ISBN : 9780230295216

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Nonlinear Financial Econometrics: Markov Switching Models, Persistence and Nonlinear Cointegration by Greg N. Gregoriou,Razvan Pascalau Pdf

This book proposes new methods to value equity and model the Markowitz efficient frontier using Markov switching models and provide new evidence and solutions to capture the persistence observed in stock returns across developed and emerging markets.

Bayesian Reasoning and Machine Learning

Author : David Barber
Publisher : Cambridge University Press
Page : 739 pages
File Size : 48,7 Mb
Release : 2012-02-02
Category : Computers
ISBN : 9781139643207

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Bayesian Reasoning and Machine Learning by David Barber Pdf

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

Author : Xuefeng Zhou
Publisher : Springer Nature
Page : 149 pages
File Size : 51,5 Mb
Release : 2020-01-01
Category : Automatic control
ISBN : 9789811562631

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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection by Xuefeng Zhou Pdf

This open access book focuses on robot introspection, which has a direct impact on physical human-robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.

Estimating General Markov Switching Models

Author : Martin D. D. Evans
Publisher : Unknown
Page : 17 pages
File Size : 51,9 Mb
Release : 1993
Category : Inflation (Finance)
ISBN : OCLC:27989019

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Estimating General Markov Switching Models by Martin D. D. Evans Pdf

Advances in Markov-Switching Models

Author : James D. Hamilton,Baldev Raj
Publisher : Springer Science & Business Media
Page : 267 pages
File Size : 49,5 Mb
Release : 2013-06-29
Category : Business & Economics
ISBN : 9783642511820

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Advances in Markov-Switching Models by James D. Hamilton,Baldev Raj Pdf

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.

Nonlinearly Perturbed Semi-Markov Processes

Author : Dmitrii Silvestrov,Sergei Silvestrov
Publisher : Springer
Page : 143 pages
File Size : 46,5 Mb
Release : 2017-09-06
Category : Mathematics
ISBN : 9783319609881

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Nonlinearly Perturbed Semi-Markov Processes by Dmitrii Silvestrov,Sergei Silvestrov Pdf

The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-Markov processes with a finite phase space. These methods are based on special time-space screening procedures for sequential phase space reduction of semi-Markov processes combined with the systematical use of operational calculus for Laurent asymptotic expansions. Effective recurrent algorithms are composed for getting asymptotic expansions, without and with explicit upper bounds for remainders, for power moments of hitting times, stationary and conditional quasi-stationary distributions for nonlinearly perturbed semi-Markov processes. These results are illustrated by asymptotic expansions for birth-death-type semi-Markov processes, which play an important role in various applications. The book will be a useful contribution to the continuing intensive studies in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will contribute to continuing extensive studies in the area and remain relevant for years to come.