Essays On Robust Long Memory Inference
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Author | : Michael Wolfgang Will |
Publisher | : |
Total Pages | : 0 |
Release | : 2018 |
Genre | : |
ISBN | : |
Long memory, robust statistics, locally stationary processes. - Langes Gedächtnis, robuste Statistik, lokal stationäre Prozesse
Author | : Yan Liu |
Publisher | : Springer Nature |
Total 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.
Author | : Jia Li |
Publisher | : |
Total Pages | : 0 |
Release | : 2022 |
Genre | : |
ISBN | : |
Author | : Liudas Giraitis |
Publisher | : |
Total Pages | : 577 |
Release | : 2012 |
Genre | : Mathematics |
ISBN | : 9781848162785 |
A discrete-time stationary stochastic process with finite variance is said to have long memory if its autocorrelations tend to zero hyperbolically in the lag, i.e. like a power of the lag, as the lag tends to infinity. The absolute sum of autocorrelations of such processes diverges and their spectral density at the origin is unbounded. This is unlike the so-called weakly dependent processes, where autocorrelations tend to zero exponentially fast and the spectral density is bounded at the origin. In a long memory process, the dependence between the current observation and the one at a distant future is persistent; whereas in the weakly dependent processes, these observations are approximately independent. This fact alone is enough to warn a person about the validity of the classical inference procedures based on the square root of the sample size standardization when data are generated by a long-term memory process.The aim of this volume is to provide a text at the graduate level from which one can learn, in a concise fashion, some basic theory and techniques of proving limit theorems for numerous statistics based on long memory processes. It also provides a guide to researchers about some of the inference problems under long memory.
Author | : Yoosoon Chang |
Publisher | : Emerald Group Publishing |
Total Pages | : 449 |
Release | : 2023-04-24 |
Genre | : Business & Economics |
ISBN | : 1837532125 |
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Author | : Dek Terrell |
Publisher | : Emerald Group Publishing |
Total Pages | : 418 |
Release | : 2020-04-15 |
Genre | : Business & Economics |
ISBN | : 1789739594 |
Including contributions spanning a variety of theoretical and applied topics in econometrics, this volume of Advances in Econometrics is published in honour of Cheng Hsiao.
Author | : Peter M. Robinson |
Publisher | : Advanced Texts in Econometrics |
Total Pages | : 396 |
Release | : 2003 |
Genre | : Business & Economics |
ISBN | : 9780199257300 |
Long memory time series are characterized by a strong dependence between distant events.
Author | : Deborah G. Mayo |
Publisher | : Cambridge University Press |
Total Pages | : 503 |
Release | : 2018-09-20 |
Genre | : Mathematics |
ISBN | : 1108563309 |
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Author | : Christopher F. Parmeter |
Publisher | : Emerald Group Publishing |
Total Pages | : 401 |
Release | : 2024-04-05 |
Genre | : Business & Economics |
ISBN | : 1837978751 |
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
Author | : David J. C. MacKay |
Publisher | : Cambridge University Press |
Total Pages | : 694 |
Release | : 2003-09-25 |
Genre | : Computers |
ISBN | : 9780521642989 |
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.