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Asymptotic Optimal Inference for Non-ergodic Models, I. V. Basawa; D. J. Scott


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Автор: I. V. Basawa; D. J. Scott
Название:  Asymptotic Optimal Inference for Non-ergodic Models
ISBN: 9780387908106
Издательство: Springer
Классификация:
ISBN-10: 0387908102
Обложка/Формат: Paperback
Страницы: 170
Вес: 0.27 кг.
Дата издания: 07.02.1983
Серия: Lecture Notes in Statistics
Язык: English
Размер: 234 x 156 x 10
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This monograph contains a comprehensive account of the recent work of the authors and other workers on large sample optimal inference for non-ergodic models. The non-ergodic family of models can be viewed as an extension of the usual Fisher-Rao model for asymptotics, referred to here as an ergodic family.


Two-Scale Stochastic Systems / Asymptotic Analysis and Control

Автор: Kabanov Yuri, Pergamenshchikov Sergei
Название: Two-Scale Stochastic Systems / Asymptotic Analysis and Control
ISBN: 3540653325 ISBN-13(EAN): 9783540653325
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.

Asymptotic theory of statistics and probability

Автор: Dasgupta, Anirban
Название: Asymptotic theory of statistics and probability
ISBN: 0387759700 ISBN-13(EAN): 9780387759708
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools.

Asymptotic Efficiency of Nonparametric Tests

Автор: Yakov Nikitin
Название: Asymptotic Efficiency of Nonparametric Tests
ISBN: 0521470293 ISBN-13(EAN): 9780521470292
Издательство: Cambridge Academ
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Цена: 18058.00 р.
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Описание: This monograph is the first unified treatment of an indispensable technique for comparing statistical tests, especially in nonparametric statistics. It presents powerful new methods to evaluate explicitly different kinds of efficiencies. Many Russian results are published here for the first time in English.

Large deviations and asymptotic methods in finance

Название: Large deviations and asymptotic methods in finance
ISBN: 3319116045 ISBN-13(EAN): 9783319116044
Издательство: Springer
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Цена: 22359.00 р.
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Описание:

Hagan, Lesniewski, Woodward: Probability Distribution in the SABR Model of Stochastic Volatility.- Paulot: Asymptotic Implied Volatility at the Second Order with Application to the SABR Model.- Henry-Labordere: Unifying the BGM and SABR Models: A Short Ride in Hyperbolic Geometry.- Ben Arous, Laurence: Second Order Expansion for Implied Volatility in Two Factor Local-stochastic Volatility.- Osajima: General Asymptotics of Wiener Functionals and Application to Implied Volatilities.- Bayer, Laurence: Small-time asymptotics for the at-the-money implied volatility in a multi-dimensional local volatility model.- Keller-Ressel, Teichmann: A Remark on Gatheral's 'Most-likely Path Approximation' of Implied Volatility.- Gatheral, Wang: Implied volatility from local volatility: a path integral approach.- Gerhold, Friz: Don't Stay Local - Extrapolation Analytics for Dupire's Local Volatility.- Gulisashvili, Teichmann: Laplace Principle Expansions and Short Time Asymptotics for Affine Processes.- Lorig, Pascucci, Pagliarani: Asymptotics for d-dimensional Levy-type Processes.- Takahashi: An Asymptotic Expansion Approach in Finance.- Baudoin, Ouyang: On small time asymptotics for rough differential equations driven by fractional Brownian motions.- Lucic: On singularities in the Heston model.- Bayer, Friz, Laurence: On the probability density function of baskets.- Conforti, De Marco, Deuschel: On small-noise equations with degenerate limiting system arising from volatility models.- Pham: Long time asymptotic problems for optimal investment.- Spiliopoulos: Systemic Risk and Default Clustering for Large Financial Systems.- Jacod, Rosenbaum: Asymptotic Properties of a Volatility Estimator.

Asymptotic Theory of Statistical Inference for Time Series

Автор: Masanobu Taniguchi; Yoshihide Kakizawa
Название: Asymptotic Theory of Statistical Inference for Time Series
ISBN: 1461270286 ISBN-13(EAN): 9781461270287
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The primary aim of this book is to provide modern statistical techniques and theory for stochastic 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.

Asymptotic Chaos Expansions in Finance

Автор: Nicolay, David
Название: Asymptotic Chaos Expansions in Finance
ISBN: 1447165055 ISBN-13(EAN): 9781447165057
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Stochastic instantaneous volatility models such as Heston, SABR or SV-LMM have mostly been developed to control the shape and joint dynamics of the implied volatility surface.

Asymptotic Expansion of a Partition Function Related to the Sinh-model

Автор: Borot
Название: Asymptotic Expansion of a Partition Function Related to the Sinh-model
ISBN: 331933378X ISBN-13(EAN): 9783319333786
Издательство: Springer
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Цена: 10760.00 р.
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Описание: This book elaborates on the asymptotic behaviour, when N is large, of certain N-dimensional integrals which typically occur in random matrices, or in 1+1 dimensional quantum integrable models solvable by the quantum separation of variables. The introduction presents the underpinning motivations for this problem, a historical overview, and a summary of the strategy, which is applicable in greater generality. The core aims at proving an expansion up to o(1) for the logarithm of the partition function of the sinh-model. This is achieved by a combination of potential theory and large deviation theory so as to grasp the leading asymptotics described by an equilibrium measure, the Riemann-Hilbert approach to truncated Wiener-Hopf in order to analyse the equilibrium measure, the Schwinger-Dyson equations and the boostrap method to finally obtain an expansion of correlation functions and the one of the partition function. This book is addressed to researchers working in random matrices, statistical physics or integrable systems, or interested in recent developments of asymptotic analysis in those fields.


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