Bootstrap Methods

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Publisher : John Wiley & Sons
ISBN 13 : 1118211596
Total Pages : 337 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Bootstrap Methods by : Michael R. Chernick

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.

Spectral Analysis for Univariate Time Series

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Publisher : Cambridge University Press
ISBN 13 : 1108776175
Total Pages : 718 pages
Book Rating : 4.1/5 (87 download)

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Book Synopsis Spectral Analysis for Univariate Time Series by : Donald B. Percival

Download or read book Spectral Analysis for Univariate Time Series written by Donald B. Percival and published by Cambridge University Press. This book was released on 2020-03-19 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.

Non-Gaussian Autoregressive-Type Time Series

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Author :
Publisher : Springer Nature
ISBN 13 : 9811681627
Total Pages : 238 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Non-Gaussian Autoregressive-Type Time Series by : N. Balakrishna

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.

Multivariate Modelling of Non-Stationary Economic Time Series

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Publisher : Springer
ISBN 13 : 113731303X
Total Pages : 508 pages
Book Rating : 4.1/5 (373 download)

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Book Synopsis Multivariate Modelling of Non-Stationary Economic Time Series by : John Hunter

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.

Time Series Analysis: Methods and Applications

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Publisher : Elsevier
ISBN 13 : 0444538631
Total Pages : 777 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Time Series Analysis: Methods and Applications by :

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

Time Series Analysis: Methods and Applications

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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.

Climate Time Series Analysis

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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.

Stochastic Modeling of Scientific Data

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Publisher : CRC Press
ISBN 13 : 135141366X
Total Pages : 384 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Stochastic Modeling of Scientific Data by : Peter Guttorp

Download or read book Stochastic Modeling of Scientific Data written by Peter Guttorp and published by CRC Press. This book was released on 2018-03-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.

Journal of the American Statistical Association

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Publisher :
ISBN 13 :
Total Pages : 610 pages
Book Rating : 4.3/5 (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 2004 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Linear Models and Time-Series Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 1119431905
Total Pages : 896 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Linear Models and Time-Series Analysis by : Marc S. Paolella

Download or read book Linear Models and Time-Series Analysis written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-12-17 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. Covers traditional time series analysis with new guidelines Provides access to cutting edge topics that are at the forefront of financial econometrics and industry Includes latest developments and topics such as financial returns data, notably also in a multivariate context Written by a leading expert in time series analysis Extensively classroom tested Includes a tutorial on SAS Supplemented with a companion website containing numerous Matlab programs Solutions to most exercises are provided in the book Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH is suitable for advanced masters students in statistics and quantitative finance, as well as doctoral students in economics and finance. It is also useful for quantitative financial practitioners in large financial institutions and smaller finance outlets.

An Introduction to Bootstrap Methods with Applications to R

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Publisher : John Wiley & Sons
ISBN 13 : 1118625412
Total Pages : 318 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis An Introduction to Bootstrap Methods with Applications to R by : Michael R. Chernick

Download or read book An Introduction to Bootstrap Methods with Applications to R written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.

An Introduction to the Bootstrap

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Author :
Publisher : CRC Press
ISBN 13 : 9780412042317
Total Pages : 456 pages
Book Rating : 4.0/5 (423 download)

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Book Synopsis An Introduction to the Bootstrap by : Bradley Efron

Download or read book An Introduction to the Bootstrap written by Bradley Efron and published by CRC Press. This book was released on 1994-05-15 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.

Non-Gaussian Autoregressive-Type Time Series

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Author :
Publisher : Springer
ISBN 13 : 9789811681615
Total Pages : 225 pages
Book Rating : 4.6/5 (816 download)

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Book Synopsis Non-Gaussian Autoregressive-Type Time Series by : N. Balakrishna

Download or read book Non-Gaussian Autoregressive-Type Time Series written by N. Balakrishna and published by Springer. This book was released on 2022-02-24 with total page 225 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.

Bootstrap Techniques for Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 9781139452021
Total Pages : 238 pages
Book Rating : 4.4/5 (52 download)

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Book Synopsis Bootstrap Techniques for Signal Processing by : Abdelhak M. Zoubir

Download or read book Bootstrap Techniques for Signal Processing written by Abdelhak M. Zoubir and published by Cambridge University Press. This book was released on 2004-05-06 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

Methods and Models in Statistics

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Publisher : Imperial College Press
ISBN 13 : 9781860945410
Total Pages : 266 pages
Book Rating : 4.9/5 (454 download)

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Book Synopsis Methods and Models in Statistics by : John A. Nelder

Download or read book Methods and Models in Statistics written by John A. Nelder and published by Imperial College Press. This book was released on 2004 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: John Nelder is one of today''s leading statisticians, having made an impact on many parts of the discipline. This book contains reviews of some of those areas, written by top researchers. It is accessible to non-specialists, and is noteworthy for its breadth of coverage.

Handbook of Computational and Numerical Methods in Finance

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Publisher : Springer Science & Business Media
ISBN 13 : 0817681809
Total Pages : 438 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Handbook of Computational and Numerical Methods in Finance by : Svetlozar T. Rachev

Download or read book Handbook of Computational and Numerical Methods in Finance written by Svetlozar T. Rachev and published by Springer Science & Business Media. This book was released on 2011-06-28 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance, and numerical analysis. The methods employed bridge the gap between financial theory and computational practice, and provide solutions for complex problems that are difficult to solve by traditional analytical methods. Although numerical methods in finance have been studied intensively in recent years, many theoretical and practical financial aspects have yet to be explored. This volume presents current research and survey articles focusing on various numerical methods in finance. The book is designed for the academic community and will also serve professional investors.

Compstat

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Publisher : Springer Science & Business Media
ISBN 13 : 3642574890
Total Pages : 654 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Compstat by : Wolfgang Härdle

Download or read book Compstat written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This COMPSTAT 2002 book contains the Keynote, Invited, and Full Contributed papers presented in Berlin, August 2002. A companion volume including Short Communications and Posters is published on CD. The COMPSTAT 2002 is the 15th conference in a serie of biannual conferences with the objective to present the latest developments in Computational Statistics and is taking place from August 24th to August 28th, 2002. Previous COMPSTATs were in Vienna (1974), Berlin (1976), Leiden (1978), Edinburgh (1980), Toulouse (1982), Pra~ue (1984), Rome (1986), Copenhagen (1988), Dubrovnik (1990), Neuchatel (1992), Vienna (1994), Barcelona (1996), Bris tol (1998) and Utrecht (2000). COMPSTAT 2002 is organised by CASE, Center of Applied Statistics and Eco nomics at Humboldt-Universitat zu Berlin in cooperation with F'reie Universitat Berlin and University of Potsdam. The topics of COMPSTAT include methodological applications, innovative soft ware and mathematical developments, especially in the following fields: statistical risk management, multivariate and robust analysis, Markov Chain Monte Carlo Methods, statistics of E-commerce, new strategies in teaching (Multimedia, In ternet), computerbased sampling/questionnaires, analysis of large databases (with emphasis on computing in memory), graphical tools for data analysis, classification and clustering, new statistical software and historical development of software.