Asymptotic Statistical Inference: A Basic Course Using R, Deshmukh Shailaja, Kulkarni Madhuri

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: 139750.00 T
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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.

Автор: Pons Odile
Название: Statistical Tests Of Nonparametric Hypotheses: Asymptotic Theory
ISBN: 981453174X ISBN-13(EAN): 9789814531740
Издательство: World Scientific Publishing
Цена: 100320.00 T
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Описание: An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals.

Автор: Lucien Le Cam
Название: Asymptotic Methods in Statistical Decision Theory
ISBN: 1461293693 ISBN-13(EAN): 9781461293699
Издательство: Springer
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Цена: 222670.00 T
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Описание: Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of detailed mathematical knowledge. An "experiment" is a mathe- matical abstraction intended to describe the basic features of an observational process if that process is contemplated in advance of its implementation.

Автор: Daniil Ryabko
Название: Asymptotic Nonparametric Statistical Analysis of Stationary Time Series
ISBN: 3030125637 ISBN-13(EAN): 9783030125639
Издательство: Springer
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Цена: 46570.00 T
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Описание: Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus a rather attractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates of convergence, even of frequencies to the mean, are not available under this assumption alone. Recently, it has been shown that, while some natural and simple problems, such as homogeneity, are indeed provably impossible to solve if one only assumes that the data is stationary (or stationary ergodic), many others can be solved with rather simple and intuitive algorithms. The latter include clustering and change point estimation among others. In this volume I summarize these results. The emphasis is on asymptotic consistency, since this the strongest property one can obtain assuming stationarity alone. While for most of the problem for which a solution is found this solution is algorithmically realizable, the main objective in this area of research, the objective which is only partially attained, is to understand what is possible and what is not possible to do for stationary time series. The considered problems include homogeneity testing (the so-called two sample problem), clustering with respect to distribution, clustering with respect to independence, change point estimation, identity testing, and the general problem of composite hypotheses testing. For the latter problem, a topological criterion for the existence of a consistent test is presented. In addition, a number of open problems is presented.

Автор: I. V. Basawa; D. J. Scott
Название: Asymptotic Optimal Inference for Non-ergodic Models
ISBN: 0387908102 ISBN-13(EAN): 9780387908106
Издательство: Springer
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Цена: 107130.00 T
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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.

Автор: Donald Dawson; Rafal Kulik; Mohamedou Ould Haye; B
Название: Asymptotic Laws and Methods in Stochastics
ISBN: 1493950118 ISBN-13(EAN): 9781493950119
Издательство: Springer
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Цена: 88500.00 T
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Описание:

Preface.- Weak Convergence of Self-normalized Sums Processes (M. Csцrgő, Z. Hu).- Precise Asymptotics in Strong Limit Theorems for Self-normalized Sums of Multidimensionally Indexed Random Variables (D. Deng, Z. Hu).- The Self-normalized Asymptotic Results for Linear Processes (M. Peligrad, H. Sang).- Some results and problems for anisotropic random walk on the plane (E. Csбki, A. Fцldes, P. Rйvйsz).- On the Area of the Largest Square Covered by a Comb-Random-Walk (P. Rйvйsz).- A Compensator Characterization of Planar Point Processes (G. Ivanoff).- Central Limit Theorem Related to MDR-method (A. Bulinski).- An Extension of a Theorem of Hechner and Heinkel (D. Li, Y. Qi, A. Rosalsky).- Quenched Invariance Principles via Martingale Approximation (M. Peligrad).- An Extended Martingale Limit Theorem with Application to Specification Test for Nonlinear Co-integrating Regression Model (Q. Wang).- Change Point Detection with Stable AR(1) Errors (A. Bazarova, I. Berkes, L. Horvath).- Change-point Detection Under Dependence Based on Two-sample U-statistics (H. Dehling, R. Fried, I. Garcia, M. Wendler).- Time Series Models in Change Point Detection Tests (E. Gombay).- Diagnostic Test for Innovations of ARMA Musing Empirical processes of Residuals (K. Ghoudi, B. Remillard).- Short Range and Long Range Dependence (M. Rosenblatt).- Kernel Method for Stationary Tails: from Discrete to Continuous (H. Dai, D. Dawson, Y. Zhao).- Central Limit Theorems and Large Deviations for Additive Functionals of Reflecting Diffusion Processes (P. Glynn, R. Wang).- Kellerer's Theorem Revisited (F. Hirsch, B. Roynette, M. Yor).- Likelihood and Ranking Methods (M. Alvo).- Asymptotic and Finite-sample Properties in Statistical Estimation (J. Jurečkovб).- Publications of Miklόs Csцrgő.

Автор: Rio Emmanuel
Название: Asymptotic Theory of Weakly Dependent Random Processes
ISBN: 3662571919 ISBN-13(EAN): 9783662571910
Издательство: Springer
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Цена: 79190.00 T
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Описание:

Introduction.- Variance of partial sums.- Algebraic moments. Elementary exponential inequalities.- Maximal inequalities and strong laws.- Central limit theorems.- Coupling and mixing.- Fuk-Nagaev inequalities, applications.- Empirical distribution functions.- Empirical processes indexed by classes of functions.- Irreducible Markov chains.- Appendices.- References.- Index.

Автор: Nicolay, David
Название: Asymptotic Chaos Expansions in Finance
ISBN: 1447165055 ISBN-13(EAN): 9781447165057
Издательство: Springer
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Цена: 93160.00 T
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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.

Автор: N. Balakrishnan; I.A.V.B. Ibragimov; V.B. Nevzorov
Название: Asymptotic Methods in Probability and Statistics with Applications
ISBN: 1461266637 ISBN-13(EAN): 9781461266631
Издательство: Springer
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Цена: 46570.00 T
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Описание: The conference was organized jointly by St. Petersburg State University, St. Petersburg branch of Mathematical Institute, and the Euler Institute, and was partially sponsored by the Russian Foundation of Basic Researches.

Автор: Petr Mandl; Marie Huskova
Название: Asymptotic Statistics
ISBN: 3790807702 ISBN-13(EAN): 9783790807707
Издательство: Springer
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Цена: 102480.00 T
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Описание: Covering a wide range of topics in the field, this volume explores research in the detection of systematic changes, series of observation, robust regression analysis, numerical empirical processes and the related areas of actuarial sciences and mathematical programming.

Автор: Borot Gaлtan, Guionnet Alice, Kozlowski Karol K.
Название: Asymptotic Expansion of a Partition Function Related to the Sinh-Model
ISBN: 3319814990 ISBN-13(EAN): 9783319814995
Издательство: Springer
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Цена: 46570.00 T
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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.

Автор: Dasgupta, Anirban
Название: Asymptotic theory of statistics and probability
ISBN: 0387759700 ISBN-13(EAN): 9780387759708
Издательство: Springer
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Цена: 93160.00 T
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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.