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Asymptotics, Nonparametrics, and Time Series

Asymptotics, Nonparametrics, and Time Series PDF Author: Subir Ghosh
Publisher: CRC Press
ISBN: 9780824700515
Category : Mathematics
Languages : en
Pages : 864

Book Description
"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."

Asymptotics, Nonparametrics, and Time Series

Asymptotics, Nonparametrics, and Time Series PDF Author: Subir Ghosh
Publisher: CRC Press
ISBN: 9780824700515
Category : Mathematics
Languages : en
Pages : 864

Book Description
"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."

Nonlinear Time Series

Nonlinear Time Series PDF Author: Jianqing Fan
Publisher: Springer Science & Business Media
ISBN: 0387693955
Category : Mathematics
Languages : en
Pages : 565

Book Description
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.

Asymptotic Theory of Statistical Inference for Time Series

Asymptotic Theory of Statistical Inference for Time Series PDF Author: Masanobu Taniguchi
Publisher: Springer Science & Business Media
ISBN: 146121162X
Category : Mathematics
Languages : en
Pages : 671

Book Description
The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA processes. A wide variety of stochastic processes, including non-Gaussian linear processes, long-memory processes, nonlinear processes, non-ergodic processes and diffusion processes are described. The authors discuss estimation and testing theory and many other relevant statistical methods and techniques.

Research Papers in Statistical Inference for Time Series and Related Models

Research Papers in Statistical Inference for Time Series and Related Models PDF Author: Yan Liu
Publisher: Springer Nature
ISBN: 9819908035
Category : Mathematics
Languages : en
Pages : 591

Book Description
This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.

Higher Order Asymptotic Theory for Nonparametric Time Series Analysis and Related Contributions

Higher Order Asymptotic Theory for Nonparametric Time Series Analysis and Related Contributions PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 462

Book Description


Higher Order Asymptotic Theory for Time Series Analysis

Higher Order Asymptotic Theory for Time Series Analysis PDF Author: Masanobu Taniguchi
Publisher:
ISBN: 9781461231554
Category :
Languages : en
Pages : 172

Book Description
This book gives higher order asymptotic results in time series analysis. Especially, higher order asymptotic optimality of estimators and power comparison of tests for ARMA processes are discussed. It covers higher order asymptotics of statistics of multivariate stationary processes. Numerical studies are given, and they show that the higher order asymptotic theory is useful and important for time series analysis. Also the validities of Edgeworth expansions of some estimators are proved for dependent situations. Many results will serve as the basis for the further theoretical development and their applications.

Cyclostationary Processes and Time Series

Cyclostationary Processes and Time Series PDF Author: Antonio Napolitano
Publisher: Academic Press
ISBN: 0081027370
Category : Technology & Engineering
Languages : en
Pages : 626

Book Description
Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology. Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features. Presents the foundations and developments of the second- and higher-order theory of cyclostationary signals Performs signal analysis using both the classical stochastic process approach and the functional approach for time series Provides applications in signal detection and estimation, filtering, parameter estimation, source location, modulation format classification, and biological signal characterization Includes algorithms for cyclic spectral analysis along with Matlab/Octave code Provides generalizations of the classical cyclostationary model in order to account for relative motion between transmitter and receiver and describe irregular statistical cyclicity in the data

Madan Lal Puri Selected Collected Works

Madan Lal Puri Selected Collected Works PDF Author: Madan Lal Puri
Publisher: VSP
ISBN: 9789067643863
Category : Science
Languages : en
Pages : 796

Book Description
Professor Puri is one of the most versatile and prolific researchers in the world in mathematical statistics. His research areas include nonparametric statistics, order statistics, limit theory under mixing, time series, splines, tests of normality, generalized inverses of matrices and related topics, stochastic processes, statistics of directional data, random sets, and fuzzy sets and fuzzy measures. His fundamental contributions in developing new rank-based methods and precise evaluation of the standard procedures, asymptotic expansions of distributions of rank statistics, as well as large deviation results concerning them, span such areas as analysis of variance, analysis of covariance, multivariate analysis, and time series, to mention a few. His in-depth analysis has resulted in pioneering research contributions to prominent journals that have substantial impact on current research. This book together with the other two volumes (Volume 1: Nonparametric Methods in Statistics and Related Topics; Volume 2: Probability Theory and Extreme Value Theory), are a concerted effort to make his research works easily available to the research community. The sheer volume of the research output by him and his collaborators, coupled with the broad spectrum of the subject matters investigated, and the great number of outlets where the papers were published, attach special significance in making these works easily accessible. The papers selected for inclusion in this work have been classified into three volumes each consisting of several parts. All three volumes carry a final part consisting of the contents of the other two, as well as the complete list of Professor Puri's publications.

Non-Linear Time Series

Non-Linear Time Series PDF Author: Kamil Feridun Turkman
Publisher: Springer
ISBN: 3319070282
Category : Mathematics
Languages : en
Pages : 255

Book Description
This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.

Nonparametric Methods in Statistics and Related Topics

Nonparametric Methods in Statistics and Related Topics PDF Author: Madan Lal Puri
Publisher: Walter de Gruyter
ISBN: 3110917815
Category : Mathematics
Languages : en
Pages : 804

Book Description
Professor Puri is one of the most versatile and prolific researchers in the world in mathematical statistics. His research areas include nonparametric statistics, order statistics, limit theory under mixing, time series, splines, tests of normality, generalized inverses of matrices and related topics, stochastic processes, statistics of directional data, random sets, and fuzzy sets and fuzzy measures. His fundamental contributions in developing new rank-based methods and precise evaluation of the standard procedures, asymptotic expansions of distributions of rank statistics, as well as large deviation results concerning them, span such areas as analysis of variance, analysis of covariance, multivariate analysis, and time series, to mention a few. His in-depth analysis has resulted in pioneering research contributions to prominent journals that have substantial impact on current research. This book together with the other two volumes (Volume 2: Probability Theory and Extreme Value Theory; Volume 3: Time Series, Fuzzy Analysis and Miscellaneous Topics), are a concerted effort to make his research works easily available to the research community. The sheer volume of the research output by him and his collaborators, coupled with the broad spectrum of the subject matters investigated, and the great number of outlets where the papers were published, attach special significance in making these works easily accessible. The papers selected for inclusion in this work have been classified into three volumes each consisting of several parts. All three volumes carry a final part consisting of the contents of the other two, as well as the complete list of Professor Puri's publications.