Elements of Distribution Theory

Author: Thomas A. Severini

Publisher: Cambridge University Press

ISBN: 1139446118

Category: Mathematics

Page: N.A

View: 4622

This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.

Distributions

Theory and Applications

Author: J.J. Duistermaat,Johan A.C. Kolk

Publisher: Springer Science & Business Media

ISBN: 9780817646752

Category: Mathematics

Page: 445

View: 2306

This textbook is an application-oriented introduction to the theory of distributions, a powerful tool used in mathematical analysis. The treatment emphasizes applications that relate distributions to linear partial differential equations and Fourier analysis problems found in mechanics, optics, quantum mechanics, quantum field theory, and signal analysis. The book is motivated by many exercises, hints, and solutions that guide the reader along a path requiring only a minimal mathematical background.

Statistical Models

Author: A. C. Davison

Publisher: Cambridge University Press

ISBN: 9781139437417

Category: Mathematics

Page: N.A

View: 8871

Models and likelihood are the backbone of modern statistics. This 2003 book gives an integrated development of these topics that blends theory and practice, intended for advanced undergraduate and graduate students, researchers and practitioners. Its breadth is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics such as likelihood and linear and generalized linear models. Each chapter contains a wide range of problems and exercises. Practicals in the S language designed to build computing and data analysis skills, and a library of data sets to accompany the book, are available over the Web.

Brownian Motion

Author: T. Hida

Publisher: Springer Science & Business Media

ISBN: 1461260302

Category: Mathematics

Page: 327

View: 1226

Following the publication of the Japanese edition of this book, several inter esting developments took place in the area. The author wanted to describe some of these, as well as to offer suggestions concerning future problems which he hoped would stimulate readers working in this field. For these reasons, Chapter 8 was added. Apart from the additional chapter and a few minor changes made by the author, this translation closely follows the text of the original Japanese edition. We would like to thank Professor J. L. Doob for his helpful comments on the English edition. T. Hida T. P. Speed v Preface The physical phenomenon described by Robert Brown was the complex and erratic motion of grains of pollen suspended in a liquid. In the many years which have passed since this description, Brownian motion has become an object of study in pure as well as applied mathematics. Even now many of its important properties are being discovered, and doubtless new and useful aspects remain to be discovered. We are getting a more and more intimate understanding of Brownian motion.

Random Graph Dynamics

Author: Rick Durrett

Publisher: Cambridge University Press

ISBN: 1139460889

Category: Mathematics

Page: N.A

View: 5267

The theory of random graphs began in the late 1950s in several papers by Erdos and Renyi. In the late twentieth century, the notion of six degrees of separation, meaning that any two people on the planet can be connected by a short chain of people who know each other, inspired Strogatz and Watts to define the small world random graph in which each site is connected to k close neighbors, but also has long-range connections. At a similar time, it was observed in human social and sexual networks and on the Internet that the number of neighbors of an individual or computer has a power law distribution. This inspired Barabasi and Albert to define the preferential attachment model, which has these properties. These two papers have led to an explosion of research. The purpose of this book is to use a wide variety of mathematical argument to obtain insights into the properties of these graphs. A unique feature is the interest in the dynamics of process taking place on the graph in addition to their geometric properties, such as connectedness and diameter.

Analysis of Multivariate and High-Dimensional Data

Author: Inge Koch

Publisher: Cambridge University Press

ISBN: 0521887933

Category: Business & Economics

Page: 526

View: 788

This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

Stochastic Processes

Author: Richard F. Bass

Publisher: Cambridge University Press

ISBN: 113950147X

Category: Mathematics

Page: N.A

View: 5110

This comprehensive guide to stochastic processes gives a complete overview of the theory and addresses the most important applications. Pitched at a level accessible to beginning graduate students and researchers from applied disciplines, it is both a course book and a rich resource for individual readers. Subjects covered include Brownian motion, stochastic calculus, stochastic differential equations, Markov processes, weak convergence of processes and semigroup theory. Applications include the Black–Scholes formula for the pricing of derivatives in financial mathematics, the Kalman–Bucy filter used in the US space program and also theoretical applications to partial differential equations and analysis. Short, readable chapters aim for clarity rather than full generality. More than 350 exercises are included to help readers put their new-found knowledge to the test and to prepare them for tackling the research literature.

Asymptotic Statistics

Author: A. W. van der Vaart

Publisher: Cambridge University Press

ISBN: 9780521784504

Category: Mathematics

Page: 443

View: 9041

A mathematically rigorous, practical introduction presenting standard topics plus research.

Markov Chains

Author: J. R. Norris

Publisher: Cambridge University Press

ISBN: 1107393477

Category: Mathematics

Page: N.A

View: 3628

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.

Design of Comparative Experiments

Author: R. A. Bailey

Publisher: Cambridge University Press

ISBN: 1139469916

Category: Mathematics

Page: N.A

View: 2148

This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.

Exercises in Probability

A Guided Tour from Measure Theory to Random Processes, Via Conditioning

Author: Loïc Chaumont,Marc Yor

Publisher: Cambridge University Press

ISBN: 1107606551

Category: Mathematics

Page: 279

View: 6801

Over 100 exercises with detailed solutions, insightful notes and references for further reading. Ideal for beginning researchers.

Bootstrap Methods and Their Application

Author: A. C. Davison,D. V. Hinkley

Publisher: Cambridge University Press

ISBN: 9780521574716

Category: Computers

Page: 582

View: 945

This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: http://statwww.epfl.ch/davison/BMA/

Asymptotic Theory of Statistics and Probability

Author: Anirban DasGupta

Publisher: Springer Science & Business Media

ISBN: 0387759700

Category: Mathematics

Page: 722

View: 2005

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.

Fundamentals of Nonparametric Bayesian Inference

Author: Subhashis Ghosal,Aad van der Vaart

Publisher: Cambridge University Press

ISBN: 0521878268

Category: Business & Economics

Page: 670

View: 6801

Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.

Measure Theory and Filtering

Introduction and Applications

Author: Lakhdar Aggoun,Robert J. Elliott

Publisher: Cambridge University Press

ISBN: 9781139456241

Category: Mathematics

Page: N.A

View: 2168

This book was published in 2004. The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus-based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.

Probability on Trees and Networks

Author: Russell Lyons,Yuval Peres

Publisher: Cambridge University Press

ISBN: 1316785335

Category: Mathematics

Page: N.A

View: 3250

Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.

Essentials of Statistical Inference

Author: G. A. Young,R. L. Smith

Publisher: Cambridge University Press

ISBN: 9780521839716

Category: Mathematics

Page: 225

View: 6501

Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between them. Computational ideas are explained, as well as basic mathematical theory. Written in a lucid and informal style, this concise text provides both basic material on the main approaches to inference, as well as more advanced material on developments in statistical theory, including: material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems.

Probability with Martingales

Author: David Williams

Publisher: Cambridge University Press

ISBN: 9780521406055

Category: Mathematics

Page: 251

View: 1514

This is a masterly introduction to the modern and rigorous theory of probability. The author adopts the martingale theory as his main theme and moves at a lively pace through the subject's rigorous foundations. Measure theory is introduced and then immediately exploited by being applied to real probability theory. Classical results, such as Kolmogorov's Strong Law of Large Numbers and Three-Series Theorem are proved by martingale techniques. A proof of the Central Limit Theorem is also given. The author's style is entertaining and inimitable with pedagogy to the fore. Exercises play a vital role; there is a full quota of interesting and challenging problems, some with hints.

Confidence, Likelihood, Probability

Author: Tore Schweder,Nils Lid Hjort

Publisher: Cambridge University Press

ISBN: 0521861608

Category: Business & Economics

Page: 544

View: 1689

This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.