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| Author | : Holger Rootzén |
| Publisher | : |
| Total Pages | : 34 |
| Release | : 1981 |
| Genre | : |
| ISBN | : |
| Author | : Mengxi Yi |
| Publisher | : Springer Nature |
| Total Pages | : 500 |
| Release | : 2023-04-19 |
| Genre | : Mathematics |
| ISBN | : 3031226879 |
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.
| Author | : M. R. Leadbetter |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 344 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461254493 |
Classical Extreme Value Theory-the asymptotic distributional theory for maxima of independent, identically distributed random variables-may be regarded as roughly half a century old, even though its roots reach further back into mathematical antiquity. During this period of time it has found significant application-exemplified best perhaps by the book Statistics of Extremes by E. J. Gumbel-as well as a rather complete theoretical development. More recently, beginning with the work of G. S. Watson, S. M. Berman, R. M. Loynes, and H. Cramer, there has been a developing interest in the extension of the theory to include, first, dependent sequences and then continuous parameter stationary processes. The early activity proceeded in two directions-the extension of general theory to certain dependent sequences (e.g., Watson and Loynes), and the beginning of a detailed theory for stationary sequences (Berman) and continuous parameter processes (Cramer) in the normal case. In recent years both lines of development have been actively pursued.
| Author | : Pavle Mladenović |
| Publisher | : Springer Nature |
| Total Pages | : 287 |
| Release | : |
| Genre | : |
| ISBN | : 3031574125 |
| Author | : Sidney I. Resnick |
| Publisher | : Springer |
| Total Pages | : 334 |
| Release | : 2013-12-20 |
| Genre | : Mathematics |
| ISBN | : 0387759530 |
This book examines the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors. It emphasizes the core primacy of three topics necessary for understanding extremes: the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces.
| Author | : |
| Publisher | : |
| Total Pages | : 904 |
| Release | : 1994 |
| Genre | : Chemistry |
| ISBN | : |
Reports NIST research and development in the physical and engineering sciences in which the Institute is active. These include physics, chemistry, engineering, mathematics, and computer sciences. Emphasis on measurement methodology and the basic technology underlying standardization.
| Author | : Evarist Giné |
| Publisher | : Cambridge University Press |
| Total Pages | : 706 |
| Release | : 2021-03-25 |
| Genre | : Mathematics |
| ISBN | : 1009022784 |
In nonparametric and high-dimensional statistical models, the classical Gauss–Fisher–Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.
| Author | : D N Shanbhag |
| Publisher | : Gulf Professional Publishing |
| Total Pages | : 1028 |
| Release | : 2003-02-24 |
| Genre | : Mathematics |
| ISBN | : 9780444500137 |
This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.
| Author | : Tailen Hsing |
| Publisher | : |
| Total Pages | : 25 |
| Release | : 1987 |
| Genre | : |
| ISBN | : |
This document describes a strictly stationary sequence of random variables which satisfies the strong mixing condition (also known as uniform or alpha-mixing). Keywords: Normalizing functions; Weak convergence; Continuous distribution; Extreme values; Point processes.
| Author | : Anirban DasGupta |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 727 |
| Release | : 2008-02-06 |
| Genre | : Mathematics |
| ISBN | : 0387759719 |
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. The book is unique in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.
