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Author : Nhu Dinh Le
Publisher :
ISBN 13 :
Total Pages : 338 pages
Book Rating : 4.:/5 (242 download)
Download or read book Modeling and Bootstrapping for Non-Gaussian Time Series written by Nhu Dinh Le and published by . This book was released on 1990 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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Author : Nhu Dinh Le
Publisher : Ann Arbor, Mich. : University Microfilms International
ISBN 13 :
Total Pages : 338 pages
Book Rating : 4.:/5 (242 download)
Download or read book Modeling and Bootstrapping for Non-Gaussian Time Series [microform] written by Nhu Dinh Le and published by Ann Arbor, Mich. : University Microfilms International. This book was released on 1990 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul Doukhan
Publisher : Springer
ISBN 13 : 3319769383
Total Pages : 322 pages
Book Rating : 4.3/5 (197 download)
Download or read book Stochastic Models for Time Series written by Paul Doukhan and published by Springer. This book was released on 2018-04-17 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit theorems) are described under SRD; mixing and weak dependence are also reviewed. In closing, it describes moment techniques together with their relations to cumulant sums as well as an application to kernel type estimation.The appendix reviews basic probability theory facts and discusses useful laws stemming from the Gaussian laws as well as the basic principles of probability, and is completed by R-scripts used for the figures. Richly illustrated with examples and simulations, the book is recommended for advanced master courses for mathematicians just entering the field of time series, and statisticians who want more mathematical insights into the background of non-linear time series.
Author : Tucker S. McElroy
Publisher : CRC Press
ISBN 13 : 1439876525
Total Pages : 587 pages
Book Rating : 4.4/5 (398 download)
Download or read book Time Series written by Tucker S. McElroy and published by CRC Press. This book was released on 2019-12-09 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.S. students. Basic theoretical results are presented in a mathematically convincing way, and the methods of data analysis are developed through examples and exercises parsed in R. A student with a basic course in mathematical statistics will learn both how to analyze time series and how to interpret the results. The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling. The second half of the book focuses on statistical inference, the fitting of time series models, as well as computational facets of forecasting. Many time series of interest are nonlinear in which case classical inference methods can fail, but bootstrap methods may come to the rescue. Distinctive features of the book are the emphasis on geometric notions and the frequency domain, the discussion of entropy maximization, and a thorough treatment of recent computer-intensive methods for time series such as subsampling and the bootstrap. There are more than 600 exercises, half of which involve R coding and/or data analysis. Supplements include a website with 12 key data sets and all R code for the book's examples, as well as the solutions to exercises.
Author : Jianqing Fan
Publisher : Springer Science & Business Media
ISBN 13 : 0387693955
Total Pages : 565 pages
Book Rating : 4.3/5 (876 download)
Download or read book Nonlinear Time Series written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2008-09-11 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.
Author : Michael R. Chernick
Publisher : John Wiley & Sons
ISBN 13 : 1118211596
Total Pages : 337 pages
Book Rating : 4.1/5 (182 download)
Download or read book Bootstrap Methods written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.
Author : Manfred Mudelsee
Publisher : Springer Science & Business Media
ISBN 13 : 9048194822
Total Pages : 497 pages
Book Rating : 4.0/5 (481 download)
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.
Author : Elizabeth Kathleen Ely
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.:/5 (211 download)
Download or read book Bootstrap and Box-Jenkins Prediction Intervals for Non-gaussian Autoregressive Models written by Elizabeth Kathleen Ely and published by . This book was released on 1989 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : N. Balakrishna
Publisher : Springer Nature
ISBN 13 : 9811681627
Total Pages : 238 pages
Book Rating : 4.8/5 (116 download)
Download or read book Non-Gaussian Autoregressive-Type Time Series written by N. Balakrishna and published by Springer Nature. This book was released on 2022-01-27 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates most of the available models in the field and provide their probabilistic and inferential properties. This book classifies the stationary time-series models into different groups such as linear stationary models with non-Gaussian innovations, linear stationary models with non-Gaussian marginal distributions, product autoregressive models and minification models. Even though several non-Gaussian time-series models are available in the literature, most of them are focusing on the model structure and the probabilistic properties.
Author : The late James Durbin
Publisher : OUP Oxford
ISBN 13 : 019964117X
Total Pages : 368 pages
Book Rating : 4.1/5 (996 download)
Download or read book Time Series Analysis by State Space Methods written by The late James Durbin and published by OUP Oxford. This book was released on 2012-05-03 with total page 368 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 providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.
Author : Kenichi Shimizu
Publisher : Springer Science & Business Media
ISBN 13 : 3834897787
Total Pages : 137 pages
Book Rating : 4.8/5 (348 download)
Download or read book Bootstrapping Stationary ARMA-GARCH Models written by Kenichi Shimizu and published by Springer Science & Business Media. This book was released on 2010-11-01 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it is widely applied for risk management. Bootstrap is without doubt a promising technique, however, it is not applicable to all time series models. A wrong application could lead to a false decision to take too much risk. Kenichi Shimizu investigates the limit of the two standard bootstrap techniques, the residual and the wild bootstrap, when these are applied to the conditionally heteroscedastic models, such as the ARCH and GARCH models. The author shows that the wild bootstrap usually does not work well when one estimates conditional heteroscedasticity of Engle’s ARCH or Bollerslev’s GARCH models while the residual bootstrap works without problems. Simulation studies from the application of the proposed bootstrap methods are demonstrated together with the theoretical investigation.
Author : Timo Teräsvirta
Publisher : OUP Oxford
ISBN 13 : 9780199587148
Total Pages : 592 pages
Book Rating : 4.5/5 (871 download)
Download or read book Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and published by OUP Oxford. This book was released on 2010-12-16 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.
Author : Peter Julian Cayton
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)
Download or read book Essays on Non-gaussian Time Series Analysis written by Peter Julian Cayton and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is a compilation of essays on the extension of financial econometric techniques to various fields of financial and non-financial risk management-- namely, longevity risk, disaster risk and food security risk. First, longevity risk is quantified by proposing a mortality forecasting methodology based on a modified survival function and nonparametric residual-based bootstrapping. The parameters of the survival function are estimated through time and are modelled with a time series model structure. The estimated model is used to generate forecasts of parameter values and life expectancy. Confidence intervals are generated by residual-based bootstrapping through an autoregressive sieve based on the estimated model. The methodology is applied to life tables of male and female subjects from the United States, Australia and Japan, and compared with the Lee-Carter model in terms of forecasting life expectancy. From the results for the three countries, the proposed survival function has better long-term forecasting performance than does the Lee-Carter model. Second, a proposed methodology for estimating disaster risk is devised using bootstrapped multivariate extreme value theory methods. A disaster risk measure called storm-at-risk is created. The risk measure can be estimated through semiparametric and nonparametric approaches and is applied to weather extremes data generated by typhoons that enter the western North Pacific basin. Robustness checks on the performance of the approaches are conducted. The semiparametric approach performs better than the nonparametric approach in longer periods, but not in smaller periods. Third, food security risk is quantified by proposing risk measures for hierarchical agricultural time series data, which are generated for national and sub-national levels. The risk measures are created by a combination of forecast reconciliation methods for hierarchical time series data and residual-based bootstrapping methods. The methodology is applied to Philippine rice production time series data that are collected from the regions and are aggregated to the macro-regional and national levels.
Author : John Hunter
Publisher : Springer
ISBN 13 : 113731303X
Total Pages : 508 pages
Book Rating : 4.1/5 (373 download)
Download or read book Multivariate Modelling of Non-Stationary Economic Time Series written by John Hunter and published by Springer. This book was released on 2017-05-08 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.
Author : J. S. Urban. Hjorth
Publisher : CRC Press
ISBN 13 : 1351458752
Total Pages : 272 pages
Book Rating : 4.3/5 (514 download)
Download or read book Computer Intensive Statistical Methods written by J. S. Urban. Hjorth and published by CRC Press. This book was released on 2017-10-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome obstacles that could not be previously solved by methods such as regression and time series modelling in the areas of economics, meteorology, and transportation.
Author :
Publisher : Elsevier
ISBN 13 : 0444538631
Total Pages : 777 pages
Book Rating : 4.4/5 (445 download)
Download or read book Time Series Analysis: Methods and Applications written by and published by Elsevier. This book was released on 2012-05-18 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The 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. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respective areas
Author : Tata Subba Rao
Publisher : Elsevier
ISBN 13 : 0444538585
Total Pages : 778 pages
Book Rating : 4.4/5 (445 download)
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.
