Hidden Markov Models for Time Series

An Introduction Using R

Author: Walter Zucchini,Iain L. MacDonald

Publisher: CRC Press

ISBN: 9781420010893

Category: Mathematics

Page: 288

View: 3815

Reveals How HMMs Can Be Used as General-Purpose Time Series Models Implements all methods in R Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. Illustrates the methodology in action After presenting the simple Poisson HMM, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference. Through examples and applications, the authors describe how to extend and generalize the basic model so it can be applied in a rich variety of situations. They also provide R code for some of the examples, enabling the use of the codes in similar applications. Effectively interpret data using HMMs This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It provides a broad understanding of the models and their uses.

Hidden Markov Models for Time Series

An Introduction Using R, Second Edition

Author: Walter Zucchini,Iain L. MacDonald,Roland Langrock

Publisher: CRC Press

ISBN: 1482253844

Category: Mathematics

Page: 370

View: 4918

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture–recapture data

Hidden Markov and Other Models for Discrete- valued Time Series

Author: Iain L. MacDonald,Walter Zucchini

Publisher: CRC Press

ISBN: 9780412558504

Category: Mathematics

Page: 256

View: 1324

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.

The Synoptic Problem and Statistics

Author: Andris Abakuks

Publisher: CRC Press

ISBN: 1466572027

Category: Mathematics

Page: 215

View: 8709

See How to Use Statistics for New Testament Interpretation The Synoptic Problem and Statistics lays the foundations for a new area of interdisciplinary research that uses statistical techniques to investigate the synoptic problem in New Testament studies, which concerns the relationships between the Gospels of Matthew, Mark, and Luke. There are potential applications of the techniques to study other sets of similar documents. Explore Hidden Markov Models for Textual Data The book provides an introductory account of the synoptic problem and relevant theories, literature, and research at a level suitable for academic and professional statisticians. For those with no special interest in biblical studies or textual analysis, the book presents core statistical material on the use of hidden Markov models to analyze binary time series. Biblical scholars interested in the synoptic problem or in the use of statistical methods for textual analysis can omit the more technical/mathematical aspects of the book. The binary time series data sets and R code used are available on the author’s website.

Bayesian Time Series Models

Author: David Barber,A. Taylan Cemgil,Silvia Chiappa

Publisher: Cambridge University Press

ISBN: 0521196760

Category: Computers

Page: 417

View: 7093

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

Dynamic Process Methodology in the Social and Developmental Sciences

Author: Jaan Valsiner,Peter C. M. Molenaar,Maria C.D.P. Lyra,Nandita Chaudhary

Publisher: Springer Science & Business Media

ISBN: 9780387959221

Category: Psychology

Page: 668

View: 1740

All psychological processes—like biological and social ones—are dynamic. Phenomena of nature, society, and the human psyche are context bound, constantly changing, and variable. This feature of reality is often not recognized in the social sciences where we operate with averaged data and with homogeneous stereotypes, and consider our consistency to be the cornerstone of rational being. Yet we are all inconsistent in our actions within a day, or from, one day to the next, and much of such inconsistency is of positive value for our survival and development. Our inconsistent behaviors and thoughts may appear chaotic, yet there is generality within this highly variable dynamic. The task of scientific methodologies—qualitative and quantitative—is to find out what that generality is. It is the aim of this handbook to bring into one framework various directions of construction of methodology of the dynamic processes that exist in the social sciences at the beginning of the 21st century. This handbook is set up to bring together pertinent methodological scholarship from all over the world, and equally from the quantitative and qualitative orientations to methodology. In addition to consolidating the pertinent knowledge base for the purposes of its further growth, this book serves the major educational role of bringing practitioners—students, researchers, and professionals interested in applications—the state of the art know-how about how to think about extracting evidence from single cases, and about the formal mathematical-statistical tools to use for these purposes.

Artificial Evolution

7th International Conference, Evolution Artificielle, EA 2005, Revised Selected Papers

Author: El-ghazali Talbi,Pierre Liardet,Pierre Collet,Evelyne Lutton,Marc Schoenauer

Publisher: Springer

ISBN: 3540335900

Category: Computers

Page: 310

View: 2599

This book constitutes the thoroughly refereed post-proceedings of the 7th International Conference on Artificial Evolution, EA 2005, held in Lille, France, in October 2005. The 26 revised full papers presented were carefully reviewed and selected from 78 submissions. The papers cover all aspects of artificial evolution: genetic programming, machine learning, combinatorial optimization, co-evolution, self-assembling, artificial life and bioinformatics.

Latent Markov Models for Longitudinal Data

Author: Francesco Bartolucci,Alessio Farcomeni,Fulvia Pennoni

Publisher: CRC Press

ISBN: 1466583711

Category: Mathematics

Page: 252

View: 3240

Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB® routines used for the examples are available on the authors’ website. The book provides you with the essential background on latent variable models, particularly the latent class model. It discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the assumptions of the basic version of the latent Markov model and introduce maximum likelihood estimation through the Expectation-Maximization algorithm. They also cover constrained versions of the basic latent Markov model, describe the inclusion of the individual covariates, and address the random effects and multilevel extensions of the model. After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference. As longitudinal data become increasingly relevant in many fields, researchers must rely on specific statistical and econometric models tailored to their application. A complete overview of latent Markov models, this book demonstrates how to use the models in three types of analysis: transition analysis with measurement errors, analyses that consider unobserved heterogeneity, and finding clusters of units and studying the transition between the clusters.

Extreme Value Methods with Applications to Finance

Author: Serguei Y. Novak

Publisher: CRC Press

ISBN: 1439835748

Category: Mathematics

Page: 399

View: 5391

Extreme value theory (EVT) deals with extreme (rare) events, which are sometimes reported as outliers. Certain textbooks encourage readers to remove outliers—in other words, to correct reality if it does not fit the model. Recognizing that any model is only an approximation of reality, statisticians are eager to extract information about unknown distribution making as few assumptions as possible. Extreme Value Methods with Applications to Finance concentrates on modern topics in EVT, such as processes of exceedances, compound Poisson approximation, Poisson cluster approximation, and nonparametric estimation methods. These topics have not been fully focused on in other books on extremes. In addition, the book covers: Extremes in samples of random size Methods of estimating extreme quantiles and tail probabilities Self-normalized sums of random variables Measures of market risk Along with examples from finance and insurance to illustrate the methods, Extreme Value Methods with Applications to Finance includes over 200 exercises, making it useful as a reference book, self-study tool, or comprehensive course text. A systematic background to a rapidly growing branch of modern Probability and Statistics: extreme value theory for stationary sequences of random variables.

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2009

12th International Conference, London, UK, September 20-24, 2009, Proceedings

Author: Guang-Zhong Yang,David J. Hawkes,Daniel Rueckert,Alison Noble,Chris Taylor

Publisher: Springer Science & Business Media

ISBN: 3642042678

Category: Computers

Page: 1037

View: 7128

The two-volume set LNCS 5761 and LNCS 5762 constitute the refereed proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, held in London, UK, in September 2009. Based on rigorous peer reviews, the program committee carefully selected 259 revised papers from 804 submissions for presentation in two volumes. The second volume includes 134 papers divided in topical sections on shape modelling and analysis; motion analyysis, physical based modelling and image reconstruction; neuro, cell and multiscale image analysis; image analysis and computer aided diagnosis; and image segmentation and analysis.

Encyclopedia of Statistical Sciences

Author: N.A

Publisher: John Wiley & Sons

ISBN: 9780471743750

Category: Mathematics

Page: 664

View: 1272

With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as the only cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer and communication science, biomedicine, psychology, and many other areas.

Global Trends in Information Systems and Software Applications

4th International Conference, ObCom 2011, Vellore, TN, India, December 9-11, 2011, Part II. Proceedings

Author: P. Venkata Krishna,M. Rajasekhara Babu,Ezendu Ariwa

Publisher: Springer

ISBN: 364229216X

Category: Computers

Page: 817

View: 7778

This 2-Volume-Set, CCIS 0269-CCIS 0270, constitutes the refereed proceedings of the International Conference on Global Trends in Computing and Communication (CCIS 0269) and the International Conference on Global Trends in Information Systems and Software Applications (CCIS 0270), ObCom 2011, held in Vellore, India, in December 2011. The 173 full papers presented together with a keynote paper and invited papers were carefully reviewed and selected from 842 submissions. The conference addresses issues associated with computing, communication and information. Its aim is to increase exponentially the participants' awareness of the current and future direction in the domains and to create a platform between researchers, leading industry developers and end users to interrelate.

Diagnostic Checks in Time Series

Author: Wai Keung Li

Publisher: CRC Press

ISBN: 9780203485606

Category: Mathematics

Page: 216

View: 6198

Diagnostic checking is an important step in the modeling process. But while the literature on diagnostic checks is quite extensive and many texts on time series modeling are available, it still remains difficult to find a book that adequately covers methods for performing diagnostic checks. Diagnostic Checks in Time Series helps to fill that gap. Author Wai Keung Li--one of the world's top authorities in time series modeling--concentrates on diagnostic checks for stationary time series and covers a range of different linear and nonlinear models, from various ARMA, threshold type, and bilinear models to conditional non-Gaussian and autoregressive heteroscedasticity (ARCH) models. Because of its broad applicability, the portmanteau goodness-of-fit test receives particular attention, as does the score test. Unlike most treatments, the author's approach is a practical one, and he looks at each topic through the eyes of a model builder rather than a mathematical statistician. This book brings together the widely scattered literature on the subject, and with clear explanations and focus on applications, it guides readers through the final stages of their modeling efforts. With Diagnostic Checks in Time Series, you will understand the relative merits of the models discussed, know how to estimate these models, and often find ways to improve a model.