Research Papers In Statistical Inference For Time Series And Related Models

Author : Yan Liu,Junichi Hirukawa,Yoshihide Kakizawa
Publisher : Springer Nature
Page : 591 pages
File Size : 55,5 Mb
Release : 2023-05-31
Category : Mathematics
ISBN : 9789819908035

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Research Papers in Statistical Inference for Time Series and Related Models by Yan Liu,Junichi Hirukawa,Yoshihide Kakizawa Pdf

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.

Author : Deborah G. Mayo
Publisher : Cambridge University Press
Page : 503 pages
File Size : 46,9 Mb
Release : 2018-09-20
Category : Mathematics
ISBN : 9781107054134

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Statistical Inference as Severe Testing by Deborah G. Mayo Pdf

Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.

Author : T. Subba Rao
Publisher : CRC Press
Page : 466 pages
File Size : 40,9 Mb
Release : 1993-07-01
Category : Mathematics
ISBN : 0412492601

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Developments in Time Series Analysis by T. Subba Rao Pdf

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.

Author : Emanuel Parzen
Publisher : Unknown
Page : 588 pages
File Size : 55,6 Mb
Release : 1967
Category : Time-series analysis
ISBN : STANFORD:36105031924348

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Time Series Analysis Papers by Emanuel Parzen Pdf

On consistent estimates of the spectral density of a stationary time series; Analysis of a general system for the detection of amplitude-modulated noise; A central limit theorem for multilinear stochastic processes; Conditions that a stochastic process ber egodic; On consistent estimates of the spectrum of a stationary time series; On choosing an estimate of the spectral density function of a stationary time series; On asymptotically efficient consistent estimates of the spectral density function of a stationary time series; General considerations in the analysis of spectra; Mathematical considerations in the estimation of spectra; Spectral analysis of asymptotically stationary time series; On spectral analysis with missing observations and amplitude modulation; Notes on fourier analysis and spectral windows; Statistical inference on time series by Hilbert space methods; An approach to time series analysis; Regression analysis of continuous parameter time series; A new approach to the synthesis of optimal smoothing and prediction systems; Probability density functionals and reproducing kernel hilbert spaces; Extraction and detection problems and reproducing kernel hilbert spaces; On estimation of a probability density function and mode; On models for the probability of fatigue failure of a structure; An approach to empirical time series analysis.

Author : Jianqing Fan,Hira L Koul
Publisher : World Scientific
Page : 552 pages
File Size : 52,5 Mb
Release : 2006-07-17
Category : Computers
ISBN : 9781908979766

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Frontiers in Statistics by Jianqing Fan,Hira L Koul Pdf

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. Contents:Our Steps on the Bickel Way (K Doksum & Y Ritov)Semiparametric Models: A Review of Progress since BKRW (1993) (J A Wellner et al.)Efficient Estimator for Time Series (A Schick & W Wefelmeyer)On the Efficiency of Estimation for a Single-Index Model (Y Xia & H Tong)Estimating Function Based Cross-Validation (M J Van der Laan & D Rubin)Powerful Choices: Tuning Parameter Selection Based on Power (K Doksum & C Schafer)Nonparametric Assessment of Atypicality (P Hall & J W Kay)Selective Review on Wavelets in Statistics (Y Wang)Model Diagnostics via Martingale Transforms: A Brief Review (H L Koul)Boosting Algorithms: With an Application to Bootstrapping Multivariate Time Series (P Bühlmann & R W Lutz)Bootstrap Methods: A Review (S N Lahiri)An Expansion for a Discrete Non-Lattice Distribution (F Götze & W R van Zwet)An Overview on Nonparametric and Semiparametric Techniques for Longitudinal Data (J Fan & R Li)Regressing Longitudinal Response Trajectories on a Covariate (H-G Müller & F Yao)Statistical Physics and Statistical Computing: A Critical Link (J D Servidea & X-L Meng)Network Tomography: A Review and Recent Developments (E Lawrence et al.)Likelihood Inference for Diffusions: A Survey (Y Aït-Sahalia)Nonparametric Estimation of Production Efficiency (B U Park et al.)Convergence and Consistency of Newton's Algorithm for Estimating Mixing Distribution (J K Ghosh & S T Tokdar)Mixed Models: An Overview (J Jiang & Z Ge)Robust Location and Scatter Estimators in Multivariate Analysis (Y Zuo)Estimation of the Loss of an Estimate (W H Wong) Readership: Advanced graduate students and researchers in statistics. Keywords:Semiparametrics;Financial Econometrics;Longitudinal Data;Efficient Estimation;Single Index;Atypicality;Martingale Transforms;Boosting;Non-Lattice Distributions;Longitudinal Data;Network Tomography;Mixed ModelsKey Features:Gathers contributions from renowned researchers such as Kjell Doksum and Peter HallA must-have volume for researchers in statistics

Author : Ignacio Rojas,Héctor Pomares,Olga Valenzuela
Publisher : Springer
Page : 340 pages
File Size : 46,7 Mb
Release : 2018-10-03
Category : Business & Economics
ISBN : 9783319969442

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Time Series Analysis and Forecasting by Ignacio Rojas,Héctor Pomares,Olga Valenzuela Pdf

This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.

Author : A.J. Tallón-Ballesteros,R. Beltrán-Barba
Publisher : IOS Press
Page : 980 pages
File Size : 49,8 Mb
Release : 2023-12-19
Category : Computers
ISBN : 9781643684710

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Fuzzy Systems and Data Mining IX by A.J. Tallón-Ballesteros,R. Beltrán-Barba Pdf

Fuzzy systems and data mining are indispensible aspects of the digital technology on which we now all depend. Fuzzy logic is intrinsic to applications in the electrical, chemical and engineering industries, and also in the fields of management and environmental issues. Data mining is indispensible in dealing with big data, massive data, and scalable, parallel and distributed algorithms. This book presents the proceedings of FSDM 2023, the 9th International Conference on Fuzzy Systems and Data Mining, held from 10-13 November 2023 as a hybrid event, with some participants attending in Chongqing, China, and others online. The conference focuses on four main areas: fuzzy theory, algorithms and systems; fuzzy application; data mining; and the interdisciplinary field of fuzzy logic and data mining, and provides a forum for experts, researchers, academics and representatives from industry to share the latest advances in the field of fuzzy sets and data mining. This year, topics from two special sessions on granular-ball computing and the application of generative AI, as well as machine learning and neural networks, were also covered. A total of 363 submissions were received, and after careful review by the members of the international program committee, 110 papers were accepted for presentation at the conference and publication here, representing an acceptance rate of just over 30%. Covering a comprehensive range of current research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Author : Chris Chatfield,Haipeng Xing
Publisher : CRC Press
Page : 398 pages
File Size : 47,5 Mb
Release : 2019-04-25
Category : Mathematics
ISBN : 9781498795647

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The Analysis of Time Series by Chris Chatfield,Haipeng Xing Pdf

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models. It also presents many examples and implementations of time series models and methods to reflect advances in the field. Highlights of the seventh edition: A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.

Author : Carlo Berzuini,Philip Dawid,Luisa Bernardinell
Publisher : John Wiley & Sons
Page : 387 pages
File Size : 50,5 Mb
Release : 2012-06-04
Category : Mathematics
ISBN : 9781119941736

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Causality by Carlo Berzuini,Philip Dawid,Luisa Bernardinell Pdf

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.

Author : David McDowall
Publisher : SAGE
Page : 100 pages
File Size : 45,6 Mb
Release : 1980-08
Category : Mathematics
ISBN : 0803914938

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Interrupted Time Series Analysis by David McDowall Pdf

Describes ARIMA or Box Tiao models, widely used in the analysis of interupted time series quasi-experiments, assuming no statistical background beyond simple correlation. The principles and concepts of ARIMA time series analyses are developed and applied where a discrete intervention has impacted a social system. '...this is the kind of exposition I wished I had had some ten years ago when venturing into the world of autoregressive, moving-average (ARIMA) models of time-series analysis...This monograph nicely lays out a method for assessing the impact of a discrete policy or event of some importance on behavior which can be continuously observed...If widely used, as I hope, it will save a generation of social scientists fro

Author : Torben Gustav Andersen,Richard A. Davis,Jens-Peter Kreiß,Thomas V. Mikosch
Publisher : Springer Science & Business Media
Page : 1045 pages
File Size : 53,6 Mb
Release : 2009-04-21
Category : Business & Economics
ISBN : 9783540712978

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Handbook of Financial Time Series by Torben Gustav Andersen,Richard A. Davis,Jens-Peter Kreiß,Thomas V. Mikosch Pdf

The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Author : United States. Defense Logistics Studies Information Exchange
Publisher : Unknown
Page : 1200 pages
File Size : 45,7 Mb
Release : 1977
Category : Military research
ISBN : MINN:31951T002489752

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Annual Department of Defense Bibliography of Logistics Studies and Related Documents by United States. Defense Logistics Studies Information Exchange Pdf

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 42,7 Mb
Release : 2024-05-21
Category : Electronic
ISBN : 9789814487191

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Advances in Statistics, Combinatorics and Related Areas by Anonim Pdf

Author : Patrick T. Brandt,John T. Williams
Publisher : SAGE
Page : 121 pages
File Size : 43,5 Mb
Release : 2007
Category : Mathematics
ISBN : 9781412906562

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Multiple Time Series Models by Patrick T. Brandt,John T. Williams Pdf

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.

Author : M. B. Rajarshi
Publisher : Springer Science & Business Media
Page : 113 pages
File Size : 48,5 Mb
Release : 2014-07-08
Category : Mathematics
ISBN : 9788132207634

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Statistical Inference for Discrete Time Stochastic Processes by M. B. Rajarshi Pdf

This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed include inference in Markov chains and extension of Markov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull, Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It further discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstrap for stationary sequences and other block based procedures are also discussed in some detail. This work can be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students.