Signal Detection in Non-Gaussian Noise, Saleem A. Kassam; John B. Thomas
Автор: Jamie D. Riggs Название: Handbook for Applied Modeling: Non-Gaussian and Correlated Data ISBN: 1316601056 ISBN-13(EAN): 9781316601051 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing data that fail idealized assumptions. It explains and demonstrates core techniques, common pitfalls and data issues, and interpretation of model results, all with a focus on application, utility, and real-life data.
Описание: This handbook brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians.
Автор: Edward J. Wegman; Stuart C. Schwartz; John B. Thom Название: Topics in Non-Gaussian Signal Processing ISBN: 1461388619 ISBN-13(EAN): 9781461388616 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Non-Gaussian Signal Processing is a child of a technological push. This in turn opens the door to a fundamental reexamination of structure and inference methods for non-Gaussian sto- chastic processes together with the application of such processes as models in the context of filtering, estimation, detection and signal extraction.
Автор: Jondeau Eric Название: Financial Modeling Under Non-Gaussian Distributions ISBN: 1849965994 ISBN-13(EAN): 9781849965996 Издательство: Springer Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practitioners and researchers who have handled financial market data know that asset returns do not behave according to the bell-shaped curve, associated with the Gaussian or normal distribution. Indeed, the use of Gaussian models when the asset return distributions are not normal could lead to a wrong choice of portfolio, the underestimation of extreme losses or mispriced derivative products. Consequently, non-Gaussian models and models based on processes with jumps, are gaining popularity among financial market practitioners.
Non-Gaussian distributions are the key theme of this book which addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. One of the main aims is to bridge the gap between the theoretical developments and the practical implementations of what many users and researchers perceive as "sophisticated" models or black boxes. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series, such as exchange and interest rates.
The authors have taken care to make the material accessible to anyone with a basic knowledge of statistics, calculus and probability, while at the same time preserving the mathematical rigor and complexity of the original models.
This book will be an essential reference for practitioners in the finance industry, especially those responsible for managing portfolios and monitoring financial risk, but it will also be useful for mathematicians who want to know more about how their mathematical tools are applied in finance, and as a text for advanced courses in empirical finance; financial econometrics and financial derivatives.
Описание: This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity.
Автор: Murray Rosenblatt Название: Gaussian and Non-Gaussian Linear Time Series and Random Fields ISBN: 1461270677 ISBN-13(EAN): 9781461270676 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed.
Автор: Jondeau Название: Financial Modeling Under Non-Gaussian Distributions ISBN: 1846284198 ISBN-13(EAN): 9781846284199 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The use of Gaussian models when the asset return distributions are not normal could lead to a wrong choice of portfolio, the underestimation of extreme losses or mispriced derivative products. This book deals with the non-Gaussian distributions and addresses the consequences of non-normality and time dependency in asset returns and option prices.
Автор: Mandjes, Michel Название: Large deviations for gaussian queues ISBN: 0470015233 ISBN-13(EAN): 9780470015230 Издательство: Wiley Рейтинг: Цена: 17891.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Demonstrates how the Gaussian traffic model arises naturally, and how the analysis of the corresponding queuing model can be performed. This text provides an introduction to Gaussian queues, and surveys research into the modelling of communications networks. It is useful for postgraduate students in applied probability, and operations research.
Описание: "Electron Correlation in Molecules ab initio Beyond Gaussian Quantum Chemistry" presents a series of articles concerning important topics in quantum chemistry, including surveys of current topics in this rapidly-developing field that has emerged at the cross section of the historically established areas of mathematics, physics, chemistry, and biology. Presents surveys of current topics in this rapidly-developing field that has emerged at the cross section of the historically established areas of mathematics, physics, chemistry, and biologyFeatures detailed reviews written by leading international researchersThe volume includes review on all the topics treated by world renown authors and cutting edge research contributions."
Автор: Marcus Название: Markov Processes, Gaussian Processes, and Local Times ISBN: 1107403758 ISBN-13(EAN): 9781107403758 Издательство: Cambridge Academ Рейтинг: Цена: 12038.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Two foremost researchers present important advances in stochastic process theory by linking well-understood (Gaussian) and less well-understood (Markov) classes of processes. It builds to this material through `mini-courses` on the relevant ingredients, which assume only measure-theoretic probability. This original, readable 2006 book is for researchers and advanced graduate students.
Автор: Rue Название: Gaussian Markov Random Fields ISBN: 1584884320 ISBN-13(EAN): 9781584884323 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Gaussian Markov Random Field (GMRF) models, most widely used in spatial statistics are presented in this, the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects.
Автор: Hu Yaozhong Название: Analysis on Gaussian Spaces ISBN: 9813142170 ISBN-13(EAN): 9789813142176 Издательство: World Scientific Publishing Цена: 24552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Written by a well-known expert in fractional stochastic calculus, this book offers a comprehensive overview of Gaussian analysis, with particular emphasis on nonlinear Gaussian functionals. In addition, it covers some topics that are not frequently encountered in other treatments, such as Littlewood-Paley-Stein, etc. This coverage makes the book a valuable addition to the literature. Many results presented in this book were hitherto available only in the research literature in the form of research papers by the author and his co-authors.'Mathematical Reviews ClippingsAnalysis of functions on the finite dimensional Euclidean space with respect to the Lebesgue measure is fundamental in mathematics. The extension to infinite dimension is a great challenge due to the lack of Lebesgue measure on infinite dimensional space. Instead the most popular measure used in infinite dimensional space is the Gaussian measure, which has been unified under the terminology of 'abstract Wiener space'.Out of the large amount of work on this topic, this book presents some fundamental results plus recent progress. We shall present some results on the Gaussian space itself such as the Brunn-Minkowski inequality, Small ball estimates, large tail estimates. The majority part of this book is devoted to the analysis of nonlinear functions on the Gaussian space. Derivative, Sobolev spaces are introduced, while the famous Poincar inequality, logarithmic inequality, hypercontractive inequality, Meyer's inequality, Littlewood-Paley-Stein-Meyer theory are given in details.This book includes some basic material that cannot be found elsewhere that the author believes should be an integral part of the subject. For example, the book includes some interesting and important inequalities, the Littlewood-Paley-Stein-Meyer theory, and the H rmander theorem. The book also includes some recent progress achieved by the author and collaborators on density convergence, numerical solutions, local times.
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