Statistical Analysis Of Stationary Time Series Classic Reprint

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Statistical Analysis of Stationary Time Series (Classic Reprint)

Author : Emeritus Professor Division of Applied Mathematics Ulf Grenander
Publisher : Forgotten Books
ISBN 13 : 9780266854616
Total Pages : 306 pages
Book Rating : 4.8/5 (546 download)

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Book Synopsis Statistical Analysis of Stationary Time Series (Classic Reprint) by : Emeritus Professor Division of Applied Mathematics Ulf Grenander

Download or read book Statistical Analysis of Stationary Time Series (Classic Reprint) written by Emeritus Professor Division of Applied Mathematics Ulf Grenander and published by Forgotten Books. This book was released on 2017-10-28 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Statistical Analysis of Stationary Time Series These schemes have been important in the development of methods for the statistical analysis of time series. They have been used with a varying degree of success to describe many types of phenomena encountered in applications. From the discussion in Chapter 1 it Will be apparent that by using these schemes, it is possible to approximate a large and important class of stationary processes, Viz. The so-called linear processes (see For this to be possible p must take large rather than small values and para meters involved in the scheme must be adjusted adequately. During the last ten years a good deal of work has been devoted to the construction of tests, estimates and confidence intervals appropriate for these schemes. We have described a few of the more important of these results in Chapter 3. In spite of the ingenuity and great theoretical interest of some of these methods, their practical applicability seems to be limited severely by the assumption that the process is a low (usually zero, first or second) order finite parameter scheme. After surveying a good deal of the applied literature devoted to statistical analysis of time series met with in practice, we have come to the following conclusion. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Forecasting: principles and practice

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

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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.

Time Series Analysis

Author : Jonathan D. Cryer
Publisher : Springer Science & Business Media
ISBN 13 : 0387759581
Total Pages : 501 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Time Series Analysis by : Jonathan D. Cryer

Download or read book Time Series Analysis written by Jonathan D. Cryer and published by Springer Science & Business Media. This book was released on 2008-04-04 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an accessible approach to understanding time series models and their applications. The ideas and methods are illustrated with both real and simulated data sets. A unique feature of this edition is its integration with the R computing environment.

Multidimensional Stationary Time Series

Author : Marianna Bolla
Publisher : CRC Press
ISBN 13 : 1000392392
Total Pages : 318 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Multidimensional Stationary Time Series by : Marianna Bolla

Download or read book Multidimensional Stationary Time Series written by Marianna Bolla and published by CRC Press. This book was released on 2021-04-29 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension reduction and prediction. Understanding the covered material requires a certain mathematical maturity, a degree of knowledge in probability theory, linear algebra, and also in real, complex and functional analysis. For this, the cited literature and the Appendix contain all necessary material. The main tools of the book include harmonic analysis, some abstract algebra, and state space methods: linear time-invariant filters, factorization of rational spectral densities, and methods that reduce the rank of the spectral density matrix. Serves to find analogies between classical results (Cramer, Wold, Kolmogorov, Wiener, Kálmán, Rozanov) and up-to-date methods for dimension reduction in multidimensional time series Provides a unified treatment for time and frequency domain inferences by using machinery of complex and harmonic analysis, spectral and Smith--McMillan decompositions. Establishes analogies between the time and frequency domain notions and calculations Discusses the Wold's decomposition and the Kolmogorov's classification together, by distinguishing between different types of singularities. Understanding the remote past helps us to characterize the ideal situation where there is a regular part at present. Examples and constructions are also given Establishes a common outline structure for the state space models, prediction, and innovation algorithms with unified notions and principles, which is applicable to real-life high frequency time series It is an ideal companion for graduate students studying the theory of multivariate time series and researchers working in this field.

Time Series Analysis: Methods and Applications

Author : Tata Subba Rao
Publisher : Elsevier
ISBN 13 : 0444538585
Total Pages : 778 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Time Series Analysis: Methods and Applications by : Tata Subba Rao

Download or read book Time Series Analysis: Methods and Applications written by Tata Subba Rao and published by Elsevier. This book was released on 2012-06-26 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.

Introduction to Time Series and Forecasting

Author : Peter J. Brockwell
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.

The Statistical Analysis of Time Series

Author : Theodore W. Anderson
Publisher : John Wiley & Sons
ISBN 13 : 1118150392
Total Pages : 722 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis The Statistical Analysis of Time Series by : Theodore W. Anderson

Download or read book The Statistical Analysis of Time Series written by Theodore W. Anderson and published by John Wiley & Sons. This book was released on 2011-09-28 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley Classics Library consists of selected books that havebecome recognized classics in their respective fields. With thesenew unabridged and inexpensive editions, Wiley hopes to extend thelife of these important works by making them available to futuregenerations of mathematicians and scientists. Currently availablein the Series: T. W. Anderson Statistical Analysis of Time SeriesT. S. Arthanari & Yadolah Dodge Mathematical Programming inStatistics Emil Artin Geometric Algebra Norman T. J. Bailey TheElements of Stochastic Processes with Applications to the NaturalSciences George E. P. Box & George C. Tiao Bayesian Inferencein Statistical Analysis R. W. Carter Simple Groups of Lie TypeWilliam G. Cochran & Gertrude M. Cox Experimental Designs,Second Edition Richard Courant Differential and Integral Calculus,Volume I Richard Courant Differential and Integral Calculus, VolumeII Richard Courant & D. Hilbert Methods of MathematicalPhysics, Volume I Richard Courant & D. Hilbert Methods ofMathematical Physics, Volume II D. R. Cox Planning of ExperimentsHarold M. S. Coxeter Introduction to Modern Geometry, SecondEdition Charles W. Curtis & Irving Reiner Representation Theoryof Finite Groups and Associative Algebras Charles W. Curtis &Irving Reiner Methods of Representation Theory with Applications toFinite Groups and Orders, Volume I Charles W. Curtis & IrvingReiner Methods of Representation Theory with Applications to FiniteGroups and Orders, Volume II Bruno de Finetti Theory ofProbability, Volume 1 Bruno de Finetti Theory of Probability,Volume 2 W. Edwards Deming Sample Design in Business Research Amosde Shalit & Herman Feshbach Theoretical Nuclear Physics, Volume1 --Nuclear Structure J. L. Doob Stochastic Processes NelsonDunford & Jacob T. Schwartz Linear Operators, Part One, GeneralTheory Nelson Dunford & Jacob T. Schwartz Linear Operators,Part Two, Spectral Theory--Self Adjoint Operators in Hilbert SpaceNelson Dunford & Jacob T. Schwartz Linear Operators, PartThree, Spectral Operators Herman Fsehbach Theoretical NuclearPhysics: Nuclear Reactions Bernard Friedman Lectures onApplications-Oriented Mathematics Gerald d. Hahn & Samuel S.Shapiro Statistical Models in Engineering Morris H. Hansen, WilliamN. Hurwitz & William G. Madow Sample Survey Methods and Theory,Volume I--Methods and Applications Morris H. Hansen, William N.Hurwitz & William G. Madow Sample Survey Methods and Theory,Volume II--Theory Peter Henrici Applied and Computational ComplexAnalysis, Volume 1--Power Series--lntegration--ConformalMapping--Location of Zeros Peter Henrici Applied and ComputationalComplex Analysis, Volume 2--Special Functions--IntegralTransforms--Asymptotics--Continued Fractions Peter Henrici Appliedand Computational Complex Analysis, Volume 3--Discrete FourierAnalysis--Cauchy Integrals--Construction of ConformalMaps--Univalent Functions Peter Hilton & Yel-Chiang Wu A Coursein Modern Algebra Harry Hochetadt Integral Equations Erwin O.Kreyezig Introductory Functional Analysis with Applications WilliamH. Louisell Quantum Statistical Properties of Radiation All HasanNayfeh Introduction to Perturbation Techniques Emanuel ParzenModern Probability Theory and Its Applications P.M. Prenter Splinesand Variational Methods Walter Rudin Fourier Analysis on Groups C.L. Siegel Topics in Complex Function Theory, Volume I--EllipticFunctions and Uniformization Theory C. L. Siegel Topics in ComplexFunction Theory, Volume II--Automorphic and Abelian integrals C. LSiegel Topics in Complex Function Theory, Volume III--AbelianFunctions & Modular Functions of Several Variables J. J. StokerDifferential Geometry J. J. Stoker Water Waves: The MathematicalTheory with Applications J. J. Stoker Nonlinear Vibrations inMechanical and Electrical Systems

Statistical Analysis of Stationary Time Series

Author : Ulf Grenander
Publisher :
ISBN 13 :
Total Pages : 314 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Statistical Analysis of Stationary Time Series by : Ulf Grenander

Download or read book Statistical Analysis of Stationary Time Series written by Ulf Grenander and published by . This book was released on 1957 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Time Series Analysis and Forecasting by Example

Author : Søren Bisgaard
Publisher : John Wiley & Sons
ISBN 13 : 1118056957
Total Pages : 346 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Time Series Analysis and Forecasting by Example by : Søren Bisgaard

Download or read book Time Series Analysis and Forecasting by Example written by Søren Bisgaard and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including: Graphical tools in time series analysis Procedures for developing stationary, non-stationary, and seasonal models How to choose the best time series model Constant term and cancellation of terms in ARIMA models Forecasting using transfer function-noise models The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets. With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.

Time Series Analysis and Its Applications

Author : Robert H. Shumway
Publisher :
ISBN 13 : 9781475732627
Total Pages : 568 pages
Book Rating : 4.7/5 (326 download)

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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:

The Analysis of Time Series

Author : Chris Chatfield
Publisher : CRC Press
ISBN 13 : 1498795641
Total Pages : 398 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis The Analysis of Time Series by : Chris Chatfield

Download or read book The Analysis of Time Series written by Chris Chatfield and published by CRC Press. This book was released on 2019-04-25 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models. It also presents many examples and implementations of time series models and methods to reflect advances in the field. Highlights of the seventh edition: A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.

Time Series Analysis

Author : James D. Hamilton
Publisher : Princeton University Press
ISBN 13 : 0691218633
Total Pages : 820 pages
Book Rating : 4.6/5 (912 download)

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Book Synopsis Time Series Analysis by : James D. Hamilton

Download or read book Time Series Analysis written by James D. Hamilton and published by Princeton University Press. This book was released on 2020-09-01 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, self-contained overview of time series analysis for students and researchers The past decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This textbook synthesizes these advances and makes them accessible to first-year graduate students. James Hamilton provides comprehensive treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems—including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter—in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. This invaluable book starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.

Hands-On Time Series Analysis with R

Author : Rami Krispin
Publisher : Packt Publishing Ltd
ISBN 13 : 1788624041
Total Pages : 438 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Hands-On Time Series Analysis with R by : Rami Krispin

Download or read book Hands-On Time Series Analysis with R written by Rami Krispin and published by Packt Publishing Ltd. This book was released on 2019-05-31 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build efficient forecasting models using traditional time series models and machine learning algorithms. Key FeaturesPerform time series analysis and forecasting using R packages such as Forecast and h2oDevelop models and find patterns to create visualizations using the TSstudio and plotly packagesMaster statistics and implement time-series methods using examples mentionedBook Description Time series analysis is the art of extracting meaningful insights from, and revealing patterns in, time series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time series analysis with R and lays the foundations you need to build forecasting models. You will learn how to preprocess raw time series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book delves into traditional forecasting models such as time series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also cover advanced time series regression models with machine learning algorithms such as Random Forest and Gradient Boosting Machine using the h2o package. By the end of this book, you will have the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods. What you will learnVisualize time series data and derive better insightsExplore auto-correlation and master statistical techniquesUse time series analysis tools from the stats, TSstudio, and forecast packagesExplore and identify seasonal and correlation patternsWork with different time series formats in RExplore time series models such as ARIMA, Holt-Winters, and moreEvaluate high-performance forecasting solutionsWho this book is for Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.

Mathematical Statistics

Author : Peter J. Bickel
Publisher : CRC Press
ISBN 13 : 1498722717
Total Pages : 422 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Mathematical Statistics by : Peter J. Bickel

Download or read book Mathematical Statistics written by Peter J. Bickel and published by CRC Press. This book was released on 2015-11-04 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors' previous volume. This second volume focuses on inference in non- and semiparametric models. It not only reexamines the procedures introduced in the first volume from a more sophisticated point o

Climate Time Series Analysis

Author : Manfred Mudelsee
Publisher : Springer Science & Business Media
ISBN 13 : 9048194822
Total Pages : 497 pages
Book Rating : 4.0/5 (481 download)

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Book Synopsis Climate Time Series Analysis by : Manfred Mudelsee

Download or read book Climate Time Series Analysis written by Manfred Mudelsee and published by Springer Science & Business Media. This book was released on 2010-08-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.

Introduction to Time Series Analysis and Forecasting

Author : Douglas C. Montgomery
Publisher : John Wiley & Sons
ISBN 13 : 1118745159
Total Pages : 670 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Introduction to Time Series Analysis and Forecasting by : Douglas C. Montgomery

Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.

Nonlinear Time Series

Author : Randal Douc
Publisher : CRC Press
ISBN 13 : 1466502347
Total Pages : 548 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Nonlinear Time Series by : Randal Douc

Download or read book Nonlinear Time Series written by Randal Douc and published by CRC Press. This book was released on 2014-01-06 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.