Asymptotics, Nonparametrics, and Time Series
Title | Asymptotics, Nonparametrics, and Time Series PDF eBook |
Author | Subir Ghosh |
Publisher | CRC Press |
Pages | 864 |
Release | 1999-02-18 |
Genre | Mathematics |
ISBN | 9780824700515 |
"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."
Asymptotic Theory of Statistical Inference for Time Series
Title | Asymptotic Theory of Statistical Inference for Time Series PDF eBook |
Author | Masanobu Taniguchi |
Publisher | Springer Science & Business Media |
Pages | 671 |
Release | 2012-12-06 |
Genre | Mathematics |
ISBN | 146121162X |
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.
Asymptotics, Nonparametrics, and Time Series
Title | Asymptotics, Nonparametrics, and Time Series PDF eBook |
Author | Subir Ghosh |
Publisher | CRC Press |
Pages | 858 |
Release | 1999-02-18 |
Genre | Mathematics |
ISBN | 1482269775 |
"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."
Research Papers in Statistical Inference for Time Series and Related Models
Title | Research Papers in Statistical Inference for Time Series and Related Models PDF eBook |
Author | Yan Liu |
Publisher | Springer Nature |
Pages | 591 |
Release | 2023-05-31 |
Genre | Mathematics |
ISBN | 9819908035 |
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.
Asymptotics in Statistics
Title | Asymptotics in Statistics PDF eBook |
Author | Lucien Le Cam |
Publisher | Springer Science & Business Media |
Pages | 299 |
Release | 2012-12-06 |
Genre | Mathematics |
ISBN | 1461211662 |
This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in that it is now more 'reader friendly' and also includes a new chapter on Gaussian and Poisson experiments, reflecting their growing role in the field. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been amplified. The volume is not intended to replace monographs on specialized subjects, but will help to place them in a coherent perspective. It thus represents a link between traditional material - such as maximum likelihood, and Wald's Theory of Statistical Decision Functions -- together with comparison and distances for experiments. Much of the material has been taught in a second year graduate course at Berkeley for 30 years.
Cyclostationary Processes and Time Series
Title | Cyclostationary Processes and Time Series PDF eBook |
Author | Antonio Napolitano |
Publisher | Academic Press |
Pages | 628 |
Release | 2019-10-24 |
Genre | Technology & Engineering |
ISBN | 0081027370 |
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
Nonparametric Methods in Statistics and Related Topics
Title | Nonparametric Methods in Statistics and Related Topics PDF eBook |
Author | Madan Lal Puri |
Publisher | Walter de Gruyter |
Pages | 804 |
Release | 2013-02-06 |
Genre | Mathematics |
ISBN | 3110917815 |
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.