Smoothness Priors Analysis Of Time Series

Author : Genshiro Kitagawa,Will Gersch
Publisher : Springer Science & Business Media
Page : 265 pages
File Size : 54,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461207610

Get Book

Smoothness Priors Analysis of Time Series by Genshiro Kitagawa,Will Gersch Pdf

Smoothness Priors Analysis of Time Series addresses some of the problems of modeling stationary and nonstationary time series primarily from a Bayesian stochastic regression "smoothness priors" state space point of view. Prior distributions on model coefficients are parametrized by hyperparameters. Maximizing the likelihood of a small number of hyperparameters permits the robust modeling of a time series with relatively complex structure and a very large number of implicitly inferred parameters. The critical statistical ideas in smoothness priors are the likelihood of the Bayesian model and the use of likelihood as a measure of the goodness of fit of the model. The emphasis is on a general state space approach in which the recursive conditional distributions for prediction, filtering, and smoothing are realized using a variety of nonstandard methods including numerical integration, a Gaussian mixture distribution-two filter smoothing formula, and a Monte Carlo "particle-path tracing" method in which the distributions are approximated by many realizations. The methods are applicable for modeling time series with complex structures.

Author : Genshiro Kitagawa,Will Gersch
Publisher : Unknown
Page : 276 pages
File Size : 52,8 Mb
Release : 1996-08-01
Category : Electronic
ISBN : 1461207622

Get Book

Smoothness Priors Analysis of Time Series by Genshiro Kitagawa,Will Gersch Pdf

Author : David Brillinger,Peter Caines,John Geweke,Emanuel Parzen,Murray Rosenblatt,Murad S. Taqqu
Publisher : Springer Science & Business Media
Page : 391 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461392965

Get Book

New Directions in Time Series Analysis by David Brillinger,Peter Caines,John Geweke,Emanuel Parzen,Murray Rosenblatt,Murad S. Taqqu Pdf

This IMA Volume in Mathematics and its Applications NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is applied. To harness its great potential, strong interaction must be encouraged among the diverse community of statisticians and other scientists whose research involves the analysis of time series data. This was the goal of the IMA Workshop on "New Directions in Time Series Analysis. " The workshop was held July 2-July 27, 1990 and was organized by a committee consisting of Emanuel Parzen (chair), David Brillinger, Murray Rosenblatt, Murad S. Taqqu, John Geweke, and Peter Caines. Constant guidance and encouragement was provided by Avner Friedman, Director of the IMA, and his very helpful and efficient staff. The workshops were organized by weeks. It may be of interest to record the themes that were announced in the IMA newsletter describing the workshop: l.

Author : Genshiro Kitagawa,Will Gersch
Publisher : Unknown
Page : 128 pages
File Size : 44,9 Mb
Release : 1982
Category : Time-series analysis
ISBN : OCLC:1076584705

Get Book

A Smoothness Priors Approach to the Modeling of Time Series with Trend and Seasonality by Genshiro Kitagawa,Will Gersch Pdf

A smoothness priors approach to the modeling of time series with trends and seasonalities is shown. An observed time series is decomposed into local polynomial trend, seasonal, globally stationary autoregressive and observation error components. Each component is characterized by an unknown variance-white noise perturbed difference equation constraint. The constraints or Bayesian smoothness priors are expressed in state-space model form. A Kalman predictor yields the likelihood for the unknown variances (hyperparameters) with a computa- tional complexity, O(N). Likelihoods are computed for different constraint order models in different subsets of constraint equation model classes. Akaike's mini- mum AIC procedure is used to select the best model fitted to the data within and between the alternative model classes. Smoothing is achieved by a smoother algorithm. Examples are shown.

Author : Viktor K. Jirsa,A.R. McIntosh
Publisher : Springer
Page : 528 pages
File Size : 42,8 Mb
Release : 2007-08-16
Category : Technology & Engineering
ISBN : 9783540715122

Get Book

Handbook of Brain Connectivity by Viktor K. Jirsa,A.R. McIntosh Pdf

Our contemporary understanding of brain function is deeply rooted in the ideas of the nonlinear dynamics of distributed networks. Cognition and motor coordination seem to arise from the interactions of local neuronal networks, which themselves are connected in large scales across the entire brain. The spatial architectures between various scales inevitably influence the dynamics of the brain and thereby its function. But how can we integrate brain connectivity amongst these structural and functional domains? Our Handbook provides an account of the current knowledge on the measurement, analysis and theory of the anatomical and functional connectivity of the brain. All contributors are leading experts in various fields concerning structural and functional brain connectivity. In the first part of the Handbook, the chapters focus on an introduction and discussion of the principles underlying connected neural systems. The second part introduces the currently available non-invasive technologies for measuring structural and functional connectivity in the brain. Part three provides an overview of the analysis techniques currently available and highlights new developments. Part four introduces the application and translation of the concepts of brain connectivity to behavior, cognition and the clinical domain.

Author : David Brillinger,Enders Anthony Robinson,Frederic Paik Schoenberg
Publisher : Springer Science & Business Media
Page : 262 pages
File Size : 51,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781468493863

Get Book

Time Series Analysis and Applications to Geophysical Systems by David Brillinger,Enders Anthony Robinson,Frederic Paik Schoenberg Pdf

This IMA Volume in Mathematics and its Applications TIME SERIES ANALYSIS AND APPLICATIONS TO GEOPHYSICAL SYSTEMS contains papers presented at a very successful workshop on the same title. The event which was held on November 12-15, 2001 was an integral part of the IMA 2001-2002 annual program on " Mathematics in the Geosciences. " We would like to thank David R. Brillinger (Department of Statistics, Uni versity of California, Berkeley), Enders Anthony Robinson (Department of Earth and Environmental Engineering, Columbia University), and Fred eric Paik Schoenberg (Department of Statistics, University of California, Los Angeles) for their superb role as workshop organizers and editors of the proceedings. We are also grateful to Robert H. Shumway (Department of Statistics, University of California, Davis) for his help in organizing the four-day event. We take this opportunity to thank the National Science Foundation for its support of the IMA. Series Editors Douglas N. Arnold, Director of the IMA Fadil Santosa, Deputy Director of the IMA v PREFACE This volume contains a collection of papers that were presented dur ing the Workshop on Time Series Analysis and Applications to Geophysical Systems at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota from November 12-15, 2001. This was part of the IMA Thematic Year on Mathematics in the Geosciences, and was the last in a series of four Workshops during the Fall Quarter dedicated to Dynamical Systems and Ergodic Theory.

Author : Hirotugu Akaike,Genshiro Kitagawa
Publisher : Springer Science & Business Media
Page : 388 pages
File Size : 47,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461221623

Get Book

The Practice of Time Series Analysis by Hirotugu Akaike,Genshiro Kitagawa Pdf

A collection of applied papers on time series, appearing here for the first time in English. The applications are primarily found in engineering and the physical sciences.

Author : Raquel Prado,Marco A. R. Ferreira,Mike West
Publisher : CRC Press
Page : 473 pages
File Size : 41,6 Mb
Release : 2021-07-27
Category : Mathematics
ISBN : 9781498747042

Get Book

Time Series by Raquel Prado,Marco A. R. Ferreira,Mike West Pdf

• Expanded on aspects of core model theory and methodology. • Multiple new examples and exercises. • Detailed development of dynamic factor models. • Updated discussion and connections with recent and current research frontiers.

Author : I. Gath,G.F. Inbar
Publisher : Springer Science & Business Media
Page : 429 pages
File Size : 43,8 Mb
Release : 2013-06-29
Category : Technology & Engineering
ISBN : 9781475790986

Get Book

Advances in Processing and Pattern Analysis of Biological Signals by I. Gath,G.F. Inbar Pdf

In recent years there has been rapid progress in the development of signal processing in general, and more specifically in the application of signal processing and pattern analysis to biological signals. Techniques, such as parametric and nonparametric spectral estimation, higher order spectral estimation, time-frequency methods, wavelet transform, and identifi cation of nonlinear systems using chaos theory, have been successfully used to elucidate basic mechanisms of physiological and mental processes. Similarly, biological signals recorded during daily medical practice for clinical diagnostic procedures, such as electroen cephalograms (EEG), evoked potentials (EP), electromyograms (EMG) and electrocardio grams (ECG), have greatly benefitted from advances in signal processing. In order to update researchers, graduate students, and clinicians, on the latest developments in the field, an International Symposium on Processing and Pattern Analysis of Biological Signals was held at the Technion-Israel Institute of Technology, during March 1995. This book contains 27 papers delivered during the symposium. The book follows the five sessions of the symposium. The first section, Processing and Pattern Analysis of Normal and Pathological EEG, accounts for some of the latest developments in the area of EEG processing, namely: time varying parametric modeling; non-linear dynamic modeling of the EEG using chaos theory; Markov analysis; delay estimation using adaptive least-squares filtering; and applications to the analysis of epileptic EEG, EEG recorded from psychiatric patients, and sleep EEG.

Author : Genshiro Kitagawa
Publisher : CRC Press
Page : 315 pages
File Size : 45,9 Mb
Release : 2010-04-21
Category : Mathematics
ISBN : 9781584889229

Get Book

Introduction to Time Series Modeling by Genshiro Kitagawa Pdf

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very im

Author : Genshiro Kitagawa
Publisher : CRC Press
Page : 262 pages
File Size : 48,6 Mb
Release : 2020-08-10
Category : Mathematics
ISBN : 9780429582622

Get Book

Introduction to Time Series Modeling with Applications in R by Genshiro Kitagawa Pdf

Praise for the first edition: [This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling. ... [It] is a valuable book, especially with its broad and accessible introduction of models in the state-space framework. –Statistics in Medicine What distinguishes this book from comparable introductory texts is the use of state-space modeling. Along with this come a number of valuable tools for recursive filtering and smoothing, including the Kalman filter, as well as non-Gaussian and sequential Monte Carlo filters. –MAA Reviews Introduction to Time Series Modeling with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal of this book is to enable readers to build their own models to understand, predict and master time series. The second edition makes it possible for readers to reproduce examples in this book by using the freely available R package TSSS to perform computations for their own real-world time series problems. This book employs the state-space model as a generic tool for time series modeling and presents the Kalman filter, the non-Gaussian filter and the particle filter as convenient tools for recursive estimation for state-space models. Further, it also takes a unified approach based on the entropy maximization principle and employs various methods of parameter estimation and model selection, including the least squares method, the maximum likelihood method, recursive estimation for state-space models and model selection by AIC. Along with the standard stationary time series models, such as the AR and ARMA models, the book also introduces nonstationary time series models such as the locally stationary AR model, the trend model, the seasonal adjustment model, the time-varying coefficient AR model and nonlinear non-Gaussian state-space models. About the Author: Genshiro Kitagawa is a project professor at the University of Tokyo, the former Director-General of the Institute of Statistical Mathematics, and the former President of the Research Organization of Information and Systems.

Author : Peter D. Congdon
Publisher : CRC Press
Page : 506 pages
File Size : 47,6 Mb
Release : 2019-09-16
Category : Mathematics
ISBN : 9780429532900

Get Book

Bayesian Hierarchical Models by Peter D. Congdon Pdf

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website

Author : K.J. Aström,B. Wittenmark
Publisher : Elsevier
Page : 463 pages
File Size : 55,7 Mb
Release : 2016-07-21
Category : Technology & Engineering
ISBN : 9781483298085

Get Book

Adaptive Systems in Control and Signal Processing 1986 by K.J. Aström,B. Wittenmark Pdf

This second IFAC workshop discusses the variety and applications of adaptive systems in control and signal processing. The various approaches to adaptive control systems are covered and their stability and adaptability analyzed. The volume also includes papers taken from two poster sessions to give a concise and comprehensive overview/treatment of this increasingly important field.

Author : Tohru Katayama,Sueo Sugimoto
Publisher : CRC Press
Page : 574 pages
File Size : 48,7 Mb
Release : 2018-10-08
Category : Technology & Engineering
ISBN : 9781482273748

Get Book

Statistical Methods in Control & Signal Processing by Tohru Katayama,Sueo Sugimoto Pdf

Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.

Author : Setsuo Arikawa,Koichi Furukawa
Publisher : Springer
Page : 380 pages
File Size : 49,6 Mb
Release : 2003-07-31
Category : Science
ISBN : 9783540468462

Get Book

Discovery Science by Setsuo Arikawa,Koichi Furukawa Pdf

This book constitutes the refereed proceedings of the Second International Conference on Discovery Science, DS'99, held in Tokyo, Japan, in December 1999. The 26 revised full papers presented together with 2 invited contributions and 25 poster presentations were carefully reviewed and selected from a total of 74 submissions. The following topics are covered in their relation to discovery science: logic, inference, algorithmic learning, heuristic search, database management, data mining, networking, inductive logic programming, abductive reasoning, machine learning, constructive programming, intelligent agents, statistical methods, visualization, HCI, etc.