Bayesian Inference of State Space Models

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Publisher : Springer Nature
ISBN 13 : 303076124X
Total Pages : 503 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Bayesian Inference of State Space Models by : Kostas Triantafyllopoulos

Download or read book Bayesian Inference of State Space Models written by Kostas Triantafyllopoulos and published by Springer Nature. This book was released on 2021-11-12 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.

Time Series Analysis by State Space Methods

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Publisher : OUP Oxford
ISBN 13 : 0191627194
Total Pages : 369 pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis Time Series Analysis by State Space Methods by : James Durbin

Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by OUP Oxford. This book was released on 2012-05-03 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.

Bayesian Filtering and Smoothing

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Publisher : Cambridge University Press
ISBN 13 : 110703065X
Total Pages : 255 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Bayesian Filtering and Smoothing by : Simo Särkkä

Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

Term Structure Modeling and Estimation in a State Space Framework

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Publisher : Springer Science & Business Media
ISBN 13 : 3540283447
Total Pages : 224 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Term Structure Modeling and Estimation in a State Space Framework by : Wolfgang Lemke

Download or read book Term Structure Modeling and Estimation in a State Space Framework written by Wolfgang Lemke and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been prepared during my work as a research assistant at the Institute for Statistics and Econometrics of the Economics Department at the University of Bielefeld, Germany. It was accepted as a Ph.D. thesis titled "Term Structure Modeling and Estimation in a State Space Framework" at the Department of Economics of the University of Bielefeld in November 2004. It is a pleasure for me to thank all those people who have been helpful in one way or another during the completion of this work. First of all, I would like to express my gratitude to my advisor Professor Joachim Frohn, not only for his guidance and advice throughout the com pletion of my thesis but also for letting me have four very enjoyable years teaching and researching at the Institute for Statistics and Econometrics. I am also grateful to my second advisor Professor Willi Semmler. The project I worked on in one of his seminars in 1999 can really be seen as a starting point for my research on state space models. I thank Professor Thomas Braun for joining the committee for my oral examination.

Inference in Hidden Markov Models

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Publisher : Springer Science & Business Media
ISBN 13 : 0387289828
Total Pages : 656 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Inference in Hidden Markov Models by : Olivier Cappé

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.

Introduction to Time Series and Forecasting

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Publisher : Springer Science & Business Media
ISBN 13 : 1475725264
Total Pages : 429 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell

Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Readings in Unobserved Components Models

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Publisher : Oxford University Press, USA
ISBN 13 : 0199278695
Total Pages : 475 pages
Book Rating : 4.1/5 (992 download)

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Book Synopsis Readings in Unobserved Components Models by : Andrew C. Harvey

Download or read book Readings in Unobserved Components Models written by Andrew C. Harvey and published by Oxford University Press, USA. This book was released on 2005 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

Selected Proceedings of the Symposium on Inference for Stochastic Processes

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Publisher : IMS
ISBN 13 : 9780940600515
Total Pages : 370 pages
Book Rating : 4.6/5 (5 download)

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Book Synopsis Selected Proceedings of the Symposium on Inference for Stochastic Processes by : Ishwar V. Basawa

Download or read book Selected Proceedings of the Symposium on Inference for Stochastic Processes written by Ishwar V. Basawa and published by IMS. This book was released on 2001 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Discrete-Valued Time Series

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Publisher : CRC Press
ISBN 13 : 1466577746
Total Pages : 484 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Handbook of Discrete-Valued Time Series by : Richard A. Davis

Download or read book Handbook of Discrete-Valued Time Series written by Richard A. Davis and published by CRC Press. This book was released on 2016-01-06 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed ca

Handbook of Research Methods and Applications in Empirical Macroeconomics

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Publisher : Edward Elgar Publishing
ISBN 13 : 0857931024
Total Pages : 627 pages
Book Rating : 4.8/5 (579 download)

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Book Synopsis Handbook of Research Methods and Applications in Empirical Macroeconomics by : Nigar Hashimzade

Download or read book Handbook of Research Methods and Applications in Empirical Macroeconomics written by Nigar Hashimzade and published by Edward Elgar Publishing. This book was released on 2013-01-01 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook concentrates on the most important issues, models and techniques for research in macroeconomics, and highlights the core methodologies and their empirical application in an accessible manner. Each chapter is largely self-contained, whilst the comprehensive introduction provides an overview of the key statistical concepts and methods. All of the chapters include the essential references for each topic and provide a sound guide for further reading. Topics covered include unit roots, non-linearities and structural breaks, time aggregation, forecasting, the Kalman filter, generalised method of moments, maximum likelihood and Bayesian estimation, vector autoregressive, dynamic stochastic general equilibrium and dynamic panel models. Presenting the most important models and techniques for empirical research, this Handbook will appeal to students, researchers and academics working in empirical macro and econometrics.

The Great American Crime Decline

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Publisher : Oxford University Press
ISBN 13 : 0199702535
Total Pages : 273 pages
Book Rating : 4.1/5 (997 download)

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Book Synopsis The Great American Crime Decline by : Franklin E. Zimring

Download or read book The Great American Crime Decline written by Franklin E. Zimring and published by Oxford University Press. This book was released on 2008-11-05 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many theories--from the routine to the bizarre--have been offered up to explain the crime decline of the 1990s. Was it record levels of imprisonment? An abatement of the crack cocaine epidemic? More police using better tactics? Or even the effects of legalized abortion? And what can we expect from crime rates in the future? Franklin E. Zimring here takes on the experts, and counters with the first in-depth portrait of the decline and its true significance. The major lesson from the 1990s is that relatively superficial changes in the character of urban life can be associated with up to 75% drops in the crime rate. Crime can drop even if there is no major change in the population, the economy or the schools. Offering the most reliable data available, Zimring documents the decline as the longest and largest since World War II. It ranges across both violent and non-violent offenses, all regions, and every demographic. All Americans, whether they live in cities or suburbs, whether rich or poor, are safer today. Casting a critical and unerring eye on current explanations, this book demonstrates that both long-standing theories of crime prevention and recently generated theories fall far short of explaining the 1990s drop. A careful study of Canadian crime trends reveals that imprisonment and economic factors may not have played the role in the U.S. crime drop that many have suggested. There was no magic bullet but instead a combination of factors working in concert rather than a single cause that produced the decline. Further--and happily for future progress, it is clear that declines in the crime rate do not require fundamental social or structural changes. Smaller shifts in policy can make large differences. The significant reductions in crime rates, especially in New York, where crime dropped twice the national average, suggests that there is room for other cities to repeat this astounding success. In this definitive look at the great American crime decline, Franklin E. Zimring finds no pat answers but evidence that even lower crime rates might be in store.

Hidden Markov Models for Time Series

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Publisher : CRC Press
ISBN 13 : 1482253844
Total Pages : 370 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Hidden Markov Models for Time Series by : Walter Zucchini

Download or read book Hidden Markov Models for Time Series written by Walter Zucchini and published by CRC Press. This book was released on 2017-12-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Journal of the American Statistical Association

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Publisher :
ISBN 13 :
Total Pages : 1788 pages
Book Rating : 4.4/5 (91 download)

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Book Synopsis Journal of the American Statistical Association by :

Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2008 with total page 1788 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Gaussian Processes for Machine Learning

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Publisher : MIT Press
ISBN 13 : 026218253X
Total Pages : 266 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Gaussian Processes for Machine Learning by : Carl Edward Rasmussen

Download or read book Gaussian Processes for Machine Learning written by Carl Edward Rasmussen and published by MIT Press. This book was released on 2005-11-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

Data Assimilation

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Publisher : Springer Science & Business Media
ISBN 13 : 3540383018
Total Pages : 285 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Data Assimilation by : Geir Evensen

Download or read book Data Assimilation written by Geir Evensen and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

Characterizations of Univariate Continuous Distributions

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Publisher : Springer
ISBN 13 : 9462391394
Total Pages : 130 pages
Book Rating : 4.4/5 (623 download)

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Book Synopsis Characterizations of Univariate Continuous Distributions by : Mohammad Ahsanullah

Download or read book Characterizations of Univariate Continuous Distributions written by Mohammad Ahsanullah and published by Springer. This book was released on 2017-04-18 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides in an organized manner characterizations of univariate probability distributions with many new results published in this area since the 1978 work of Golambos & Kotz "Characterizations of Probability Distributions" (Springer), together with applications of the theory in model fitting and predictions.

Dynamic Linear Models with R

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Publisher : Springer Science & Business Media
ISBN 13 : 0387772383
Total Pages : 258 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Dynamic Linear Models with R by : Giovanni Petris

Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.