Research Papers In Statistical Inference For Time Series And Related Models
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Research Papers In Statistical Inference For Time Series And Related Models
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Author : Yan Liu
language : en
Publisher: Springer Nature
Release Date : 2023-05-31
Research Papers In Statistical Inference For Time Series And Related Models written by Yan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Mathematics categories.
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.
Developments In Time Series Analysis
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Author : T. Subba Rao
language : en
Publisher: CRC Press
Release Date : 1993-07-01
Developments In Time Series Analysis written by T. Subba Rao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-07-01 with Mathematics categories.
This volume contains 27 papers, written by time series analysts, dealing with statistical theory, methodology and applications. The emphasis is on the recent developments in the analysis of linear, onlinear (non-Gaussian), stationary and nonstationary time series. The topics include cointegration, estimation and asymptotic theory, Kalman filtering, nonparametric statistical inference, long memory models, nonlinear models, spectral analysis of stationary and nonstationary processes. Quite a number of papers are devoted to modelling and analysis of real time series, and the econometricians, mathematical statisticians, communications engineers and scientists who use time series techniques and Fourier analysis should find the papers in this volume useful.
Causality
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Author : Carlo Berzuini
language : en
Publisher: John Wiley & Sons
Release Date : 2012-06-04
Causality written by Carlo Berzuini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-04 with Mathematics categories.
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book: Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addresses examples from medicine, biology, economics and political science to aid the reader's understanding. Is authored by leading experts in their field. Is written in an accessible style. Postgraduates, professional statisticians and researchers in academia and industry will benefit from this book.
Frontiers In Statistics
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Author : Jianqing Fan
language : en
Publisher: World Scientific
Release Date : 2006-07-17
Frontiers In Statistics written by Jianqing Fan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-17 with Mathematics categories.
During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel's distinguished contributions.
Statistical Inference For Some Nonlinear Time Series Models
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Author : Chun-shan Wong
language : en
Publisher:
Release Date : 1998
Statistical Inference For Some Nonlinear Time Series Models written by Chun-shan Wong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematical statistics categories.
Contemporary Developments In Statistical Theory
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Author : Soumendra Lahiri
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-02
Contemporary Developments In Statistical Theory written by Soumendra Lahiri and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-02 with Mathematics categories.
This volume highlights Prof. Hira Koul’s achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others. Chapters are all original papers that explore the frontiers of these areas and will assist researchers and graduate students working in Statistics, Econometrics and related areas. Prof. Hira Koul was the first Ph.D. student of Prof. Peter Bickel. His distinguished career in Statistics includes the receipt of many prestigious awards, including the Senior Humbolt award (1995), and dedicated service to the profession through editorial work for journals and through leadership roles in professional societies, notably as the past president of the International Indian Statistical Association. Prof. Hira Koul has graduated close to 30 Ph.D. students, and made several seminal contributions in about 125 innovative research papers. The long list of his distinguished collaborators is represented by the contributors to this volume.
Probability And Statistical Inference
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Author : Miltiadis C. Mavrakakis
language : en
Publisher: CRC Press
Release Date : 2021-03-28
Probability And Statistical Inference written by Miltiadis C. Mavrakakis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-28 with Mathematics categories.
Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting. Features: •Complete introduction to mathematical probability, random variables, and distribution theory. •Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes. •Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference. •Detailed introduction to Bayesian statistics and associated topics. •Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC). This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.
Advances In Statistics Combinatorics And Related Areas Selected Papers From The Scra2001 Fim Viii Procs Of The Wollongong Conference
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Author : Chandra Gulati
language : en
Publisher: World Scientific
Release Date : 2002-12-19
Advances In Statistics Combinatorics And Related Areas Selected Papers From The Scra2001 Fim Viii Procs Of The Wollongong Conference written by Chandra Gulati and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-12-19 with Mathematics categories.
This book is a collection of selected refereed papers presented at the International Conference on Statistics, Combinatorics and Related Areas, and the Eighth International Conference of the Forum for Interdisciplinary Mathematics. It includes contributions from eminent statisticians such as Joe Gani, Clive Granger, Chris Heyde, R Nishii, C R Rao, P K Sen and Sue Wilson. By exploring and investigating deeper, these papers enlarge the reservoir in the represented areas of research, such as bioinformatics, estimating functions, financial statistics, generalized linear models, goodness of fit, image analysis, industrial data analysis, multivariate statistics, neural networks, quasi-likelihood, sample surveys, statistical inference, stochastic models, and time series.
Statistical Inference For Autoregressive Time Series Models
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Author : 王迪
language : en
Publisher:
Release Date : 2020
Statistical Inference For Autoregressive Time Series Models written by 王迪 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Time-series analysis categories.
Multiple Time Series Models
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Author : Patrick T. Brandt
language : en
Publisher: SAGE
Release Date : 2007
Multiple Time Series Models written by Patrick T. Brandt and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.