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Author: Charles Stein
Publisher: IMS
ISBN: 9780940600089
Category : Mathematics
Languages : en
Pages : 172
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Book Description
Author: Charles Stein
Publisher: IMS
ISBN: 9780940600089
Category : Mathematics
Languages : en
Pages : 172
Get Book Here
Book Description
Author: Charles Stein
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 216
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Book Description
Author: D N Shanbhag
Publisher: Gulf Professional Publishing
ISBN: 9780444500144
Category : Mathematics
Languages : en
Pages : 990
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Book Description
This volume in the series contains chapters on areas such as pareto processes, branching processes, inference in stochastic processes, Poisson approximation, Levy processes, and iterated random maps and some classes of Markov processes. Other chapters cover random walk and fluctuation theory, a semigroup representation and asymptomatic behavior of certain statistics of the Fisher-Wright-Moran coalescent, continuous-time ARMA processes, record sequence and their applications, stochastic networks with product form equilibrium, and stochastic processes in insurance and finance. Other subjects include renewal theory, stochastic processes in reliability, supports of stochastic processes of multiplicity one, Markov chains, diffusion processes, and Ito's stochastic calculus and its applications. c. Book News Inc.
Author: David J. Aldous
Publisher: American Mathematical Soc.
ISBN: 9780821870853
Category : Mathematics
Languages : en
Pages : 240
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Book Description
This book contains eleven articles surveying emerging topics in discrete probability. The papers are based on talks given by experts at the DIMACS "Microsurveys in Discrete Probability" workshop held at the Institute for Advanced Study, Princeton, NJ, in 1997. This compilation of current research in discrete probability provides a unique overview that is not available elsewhere in book or survey form. Topics covered in the volume include: Markov chains (pefect sampling, coupling from the past, mixing times), random trees (spanning trees on infinite graphs, enumeration of trees and forests, tree-valued Markov chains), distributional estimates (method of bounded differences, Stein-Chen method for normal approximation), dynamical percolation, Poisson processes, and reconstructing random walk from scenery.
Author: Andrew Barbour
Publisher: World Scientific
ISBN: 9814480657
Category : Mathematics
Languages : en
Pages : 239
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Book Description
A common theme in probability theory is the approximation of complicated probability distributions by simpler ones, the central limit theorem being a classical example. Stein's method is a tool which makes this possible in a wide variety of situations. Traditional approaches, for example using Fourier analysis, become awkward to carry through in situations in which dependence plays an important part, whereas Stein's method can often still be applied to great effect. In addition, the method delivers estimates for the error in the approximation, and not just a proof of convergence. Nor is there in principle any restriction on the distribution to be approximated; it can equally well be normal, or Poisson, or that of the whole path of a random process, though the techniques have so far been worked out in much more detail for the classical approximation theorems.This volume of lecture notes provides a detailed introduction to the theory and application of Stein's method, in a form suitable for graduate students who want to acquaint themselves with the method. It includes chapters treating normal, Poisson and compound Poisson approximation, approximation by Poisson processes, and approximation by an arbitrary distribution, written by experts in the different fields. The lectures take the reader from the very basics of Stein's method to the limits of current knowledge.
Author: Madan Lal Puri
Publisher: Walter de Gruyter
ISBN: 3110917823
Category : Mathematics
Languages : en
Pages : 760
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Book Description
Author: Madan Lal Puri
Publisher: VSP
ISBN: 9789067643856
Category : Science
Languages : en
Pages : 760
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Book Description
Professor Puri is one of the most versatile and prolific researchers in the world in mathematical statistics. His research areas include nonparametric statistics, order statistics, limit theory under mixing, time series, splines, tests of normality, generalized inverses of matrices and related topics, stochastic processes, statistics of directional data, random sets, and fuzzy sets and fuzzy measures. His fundamental contributions in developing new rank-based methods and precise evaluation of the standard procedures, asymptotic expansions of distributions of rank statistics, as well as large deviation results concerning them, span such areas as analysis of variance, analysis of covariance, multivariate analysis, and time series, to mention a few. His in-depth analysis has resulted in pioneering research contributions to prominent journals that have substantial impact on current research. This book together with the other two volumes (Volume 1: Nonparametric Methods in Statistics and Related Topics; Volume 3: Time Series, Fuzzy Analysis and Miscellaneous Topics), are a concerted effort to make his research works easily available to the research community. The sheer volume of the research output by him and his collaborators, coupled with the broad spectrum of the subject matters investigated, and the great number of outlets where the papers were published, attach special significance in making these works easily accessible. The papers selected for inclusion in this work have been classified into three volumes each consisting of several parts. All three volumes carry a final part consisting of the contents of the other two, as well as the complete list of Professor Puri'spublications.
Author: O.E. Barndorff-Nielsen
Publisher: CRC Press
ISBN: 9781420035988
Category : Mathematics
Languages : en
Pages : 306
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Book Description
Complex stochastic systems comprises a vast area of research, from modelling specific applications to model fitting, estimation procedures, and computing issues. The exponential growth in computing power over the last two decades has revolutionized statistical analysis and led to rapid developments and great progress in this emerging field. In Complex Stochastic Systems, leading researchers address various statistical aspects of the field, illustrated by some very concrete applications. A Primer on Markov Chain Monte Carlo by Peter J. Green provides a wide-ranging mixture of the mathematical and statistical ideas, enriched with concrete examples and more than 100 references. Causal Inference from Graphical Models by Steffen L. Lauritzen explores causal concepts in connection with modelling complex stochastic systems, with focus on the effect of interventions in a given system. State Space and Hidden Markov Models by Hans R. Künschshows the variety of applications of this concept to time series in engineering, biology, finance, and geophysics. Monte Carlo Methods on Genetic Structures by Elizabeth A. Thompson investigates special complex systems and gives a concise introduction to the relevant biological methodology. Renormalization of Interacting Diffusions by Frank den Hollander presents recent results on the large space-time behavior of infinite systems of interacting diffusions. Stein's Method for Epidemic Processes by Gesine Reinert investigates the mean field behavior of a general stochastic epidemic with explicit bounds. Individually, these articles provide authoritative, tutorial-style exposition and recent results from various subjects related to complex stochastic systems. Collectively, they link these separate areas of study to form the first comprehensive overview of this rapidly developing field.
Author: Gerold Alsmeyer
Publisher: Springer Science & Business Media
ISBN: 364238806X
Category : Mathematics
Languages : en
Pages : 265
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Book Description
Random Matrices are one of the major research areas in modern probability theory, due to their prominence in many different fields such as nuclear physics, statistics, telecommunication, free probability, non-commutative geometry, and dynamical systems. A great deal of recent work has focused on the study of spectra of large random matrices on the one hand and on iterated random functions, especially random difference equations, on the other. However, the methods applied in these two research areas are fairly dissimilar. Motivated by the idea that tools from one area could potentially also be helpful in the other, the volume editors have selected contributions that present results and methods from random matrix theory as well as from the theory of iterated random functions. This work resulted from a workshop that was held in Münster, Germany in 2011. The aim of the workshop was to bring together researchers from two fields of probability theory: random matrix theory and the theory of iterated random functions. Random matrices play fundamental, yet very different roles in the two fields. Accordingly, leading figures and young researchers gave talks on their field of interest that were also accessible to a broad audience.
Author: Persi Diaconis
Publisher: IMS
ISBN: 9780940600621
Category : Mathematics
Languages : en
Pages : 154
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Book Description
"These papers were presented and developed as expository talks at a summer-long workshop on Stein's method at Stanford's Department of Statistics in 1998."--P. iii.
