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Interrelationships Between Autoregressive And Moving Average Models The Arma Model General Considerations In M Dimensions
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Book Synopsis Interrelationships Between Autoregressive and Moving Average Models--the ARMA Model: General Considerations in M Dimensions by : C. Oprian
Download or read book Interrelationships Between Autoregressive and Moving Average Models--the ARMA Model: General Considerations in M Dimensions written by C. Oprian and published by . This book was released on 1978 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper describes a general linear stochastic model which supposes a time series to be generated by a linear aggregation of random shocks at various temporal and spatial locations. (Author).
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Book Synopsis Autoregressive Moving-average (ARMA) Model Identification for Degenerate Time Series with Application to Maneuvering Target Tracking by : Norman Owen Speakman
Download or read book Autoregressive Moving-average (ARMA) Model Identification for Degenerate Time Series with Application to Maneuvering Target Tracking written by Norman Owen Speakman and published by . This book was released on 1985 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research was conducted in the general areas of time series analysis and stochastic realization. Results were then applied to the specific problem of tracking a highly maneuverable aircraft target. An algorithm was developed to identify the order and parameters of the minimum autoregressive moving-average (ARMA) model of a multi-variable system given the output autocorrelation sequence. Studies were also conducted in the area of degenerate time series modeling. It was found that degeneracy in vector-valued time series is caused by the presence of one or more deterministic relationships in the time series. ARMA models for degenerate time series can be identified by finding and extracting the deterministic relationships from the time series. The result is a reduced dimension atochastic model of the system, The model found will have fewer white noise inputs than outputs. An AR
Book Synopsis ARMA Model Identification by : ByoungSeon Choi
Download or read book ARMA Model Identification written by ByoungSeon Choi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last two decades, considerable progress has been made in statistical time series analysis. The aim of this book is to present a survey of one of the most active areas in this field: the identification of autoregressive moving-average models, i.e., determining their orders. Readers are assumed to have already taken one course on time series analysis as might be offered in a graduate course, but otherwise this account is self-contained. The main topics covered include: Box-Jenkins' method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn's method, instrumental regression, and a range of pattern identification methods. Rather than cover all the methods in detail, the emphasis is on exploring the fundamental ideas underlying them. Extensive references are given to the research literature and as a result, all those engaged in research in this subject will find this an invaluable aid to their work.
Book Synopsis Characterization and Estimation of Two-Dimensional ARMA (Autoregressive Moving Average) Models by : R. L. Kashyap
Download or read book Characterization and Estimation of Two-Dimensional ARMA (Autoregressive Moving Average) Models written by R. L. Kashyap and published by . This book was released on 1983 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: A class of finite order two dimensional autoregressive moving average (ARMA) is introduced having the ability to represent any process with rational spectral density. In this model, the driving noise is correlated and need not be Gaussian. Currently known classes of ARMA models of AR models are shown to be subsets of the above class. This document discusses the three definitions of markov property and precisely states the class of ARMA model having the noncausal and semicausal markov property without imposing any specific boundary conditions. Next it considers the estimation of parameters of a model to fit a given image. Two approaches are considered. The first method uses only the empirical correlations and involves the solution of linear equations. The second method is the likelihood approach. Since the exact likelihood function is difficult to compute, the author resorts to approximations suggested by the torodial models. The quality of th two estimation schemes are compared via numerical experiments. Finally, he considers the problem of synthesizing a texture obeying an ARMA model. (Author).
Book Synopsis Fuzzy Systems & Operations Research and Management by : Bing-Yuan Cao
Download or read book Fuzzy Systems & Operations Research and Management written by Bing-Yuan Cao and published by Springer. This book was released on 2015-07-31 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes results of the seventh International Conference on Fuzzy Information and Engineering (ICFIE'2014) and the 1st International Conference of Operations Research and Management (ICORM'2014) on November 7-11, 2014 in ZhuHai, China. The book, contains 35 selected high-quality papers, and is divided into five main parts: Part I focuses on ``Fuzzy Systems and Its Applications", Part II on ``Fuzzy Mathematics and Its Applications", Part III discusses ``Fuzzy Information and Computer", Part IV is devoted to ``Operations Research and Management and Its Applications" and Part V includes various other topics.
Download or read book Modeling and Simulation written by and published by . This book was released on 1980 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Theory and Method Abstracts by :
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 1992 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Statistics Subject Indexes from Mathematical Reviews by : American Mathematical Society
Download or read book Statistics Subject Indexes from Mathematical Reviews written by American Mathematical Society and published by . This book was released on 1987 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Partially Nonstationary Multivariate Autoregressive Moving Average Models by : Sook Fwe Yap
Download or read book Partially Nonstationary Multivariate Autoregressive Moving Average Models written by Sook Fwe Yap and published by . This book was released on 1992 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Reviews written by and published by . This book was released on 1999 with total page 772 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Book Synopsis An Introduction to Discrete-Valued Time Series by : Christian H. Weiss
Download or read book An Introduction to Discrete-Valued Time Series written by Christian H. Weiss and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: A much-needed introduction to the field of discrete-valued time series, with a focus on count-data time series Time series analysis is an essential tool in a wide array of fields, including business, economics, computer science, epidemiology, finance, manufacturing and meteorology, to name just a few. Despite growing interest in discrete-valued time series—especially those arising from counting specific objects or events at specified times—most books on time series give short shrift to that increasingly important subject area. This book seeks to rectify that state of affairs by providing a much needed introduction to discrete-valued time series, with particular focus on count-data time series. The main focus of this book is on modeling. Throughout numerous examples are provided illustrating models currently used in discrete-valued time series applications. Statistical process control, including various control charts (such as cumulative sum control charts), and performance evaluation are treated at length. Classic approaches like ARMA models and the Box-Jenkins program are also featured with the basics of these approaches summarized in an Appendix. In addition, data examples, with all relevant R code, are available on a companion website. Provides a balanced presentation of theory and practice, exploring both categorical and integer-valued series Covers common models for time series of counts as well as for categorical time series, and works out their most important stochastic properties Addresses statistical approaches for analyzing discrete-valued time series and illustrates their implementation with numerous data examples Covers classical approaches such as ARMA models, Box-Jenkins program and how to generate functions Includes dataset examples with all necessary R code provided on a companion website An Introduction to Discrete-Valued Time Series is a valuable working resource for researchers and practitioners in a broad range of fields, including statistics, data science, machine learning, and engineering. It will also be of interest to postgraduate students in statistics, mathematics and economics.
Book Synopsis Time Series Analysis and Its Applications by : Robert H. Shumway
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of the Statistical Computing Section by : American Statistical Association. Statistical Computing Section
Download or read book Proceedings of the Statistical Computing Section written by American Statistical Association. Statistical Computing Section and published by . This book was released on 1979 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Applied Probability and Random Processes by : Oliver Ibe
Download or read book Fundamentals of Applied Probability and Random Processes written by Oliver Ibe and published by Academic Press. This book was released on 2014-06-13 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. Demonstrates concepts with more than 100 illustrations, including 2 dozen new drawings Expands readers’ understanding of disruptive statistics in a new chapter (chapter 8) Provides new chapter on Introduction to Random Processes with 14 new illustrations and tables explaining key concepts. Includes two chapters devoted to the two branches of statistics, namely descriptive statistics (chapter 8) and inferential (or inductive) statistics (chapter 9).
