Stochastics

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Mathematical Methods of Reliability Theory discusses fundamental concepts of probability theory, mathematical statistics, and an exposition of the relationships among the fundamental quantitative characteristics encountered in the theory.

This book provides an in-depth account of modern methods used to bound the supremum of stochastic processes.

The theory of dynamic games continues to evolve, and one purpose of this volume is to report a number of recent theoretical advances in the ?

This textbook provides a unified account of estimating the survival function, hazard rate, cumulative hazard, density, regression, conditional distributions, and linear functionals for the current status censored and right-censored data.

An Introduction to Stochastic Orders discusses this powerful tool that can be used in comparing probabilistic models in different areas such as reliability, survival analysis, risks, finance, and economics.

The theory of probability began in the seventeenth century with attempts to calculate the odds of winning in certain games of chance.

This book focuses on the development of approximation-related algorithms and their relevant applications.

This book provides a comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes.

The concept of conditional specification is not new.

This book will cover heuristic optimization techniques and applications in engineering problems.

Comprehensive guide to stochastic processes.

This book presents the probabilistic methods around Hardy martingales for applications to complex, harmonic, and functional analysis.

Probabilistic modeling and analysis of spatial telecommunication systems have never been more important than they are today.

In the fall of 1999, I was asked to teach a course on computer intrusion detection for the Department of Mathematical Sciences of The Johns Hopkins University.

Probabilistic analysis is increasing in popularity and importance within engineering and the applied sciences.

The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data.

Dies ist eine Einführung in die Theorie der (Wahrscheinlichkeiten der) großen Abweichungen, die mit Hilfe analytischer Methoden die exponentielle Abfallrate sehr kleiner Wahrscheinlichkeiten charakterisiert.

This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting.

Provides a graduate-level introduction to the theory of semigroups of operators.

This IMA Volume in Mathematics and its Applications STOCHASTIC MODELS IN GEOSYSTEMS is based on the proceedings of a workshop with the same title and was an integral part of the 1993-94 IMA program on "e;Emerging Applications of Probability.

This book presents the second part of a two-volume series devoted to a sys- tematic exposition of some recent developments in the theory of discrete- time Markov control processes (MCPs).

Since our first edition of this book, many developments in statistical mod- elling based on generalized linear models have been published, and our primary aim is to bring the book up to date.

The papers contained in this volume are an indication of the topics th discussed and the interests of the participants of The 9 International Conference on Probability in Banach Spaces, held at Sandjberg, Denmark, August 16-21, 1993.

For students in pure and applied probability; lots of applications, fairly self-contained.

As a student I discovered in our library a thin booklet by Frederick Mosteller entitled50 Challenging Problems in Probability.

Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics.

This textbook, which is based on the second edition of a book that has been previously published in German language, provides a comprehension-oriented introduction to asymptotic stochastics.

The book describes the possibility of making a probabilistic prognosis, which uses the mean n-day logarithm of case numbers in the past to determine an exponent for a probability density for a prognosis, as well as the particle emission concept, which is derived from contact and distribution rates that increase the exponent of the probable development to the extent that a group of people can be formed.

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In the past half-century the theory of probability has grown from a minor isolated theme into a broad and intensive discipline interacting with many other branches of mathematics.

The author, the founder of the Greek Statistical Institute, has based this book on the two volumes of his Greek edition which has been used by over ten thousand students during the past fifteen years.

In 1954, prior to the era of modem high speed computers, Leo A.

From classical foundations to modern theory, this comprehensive guide to probability interweaves mathematical proofs, historical context and detailed illustrative applications.

Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right.

This book aims to provide a self-contained introduction to the local geometry of the stochastic flows.

This book aims to introduce readers without a strong mathematical background to the basic ideas of fuzzy set theory and logic.

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.

Many probability books are written by mathematicians and have the built-in bias that the reader is assumed to be a mathematician coming to the material for its beauty.

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.

Develops the theory of Markov and semi-Markov processes in an elementary setting suitable for senior undergraduate and graduate students.

This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change.

With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs).

This book provides a rigorous introduction to the theory, computation, and applications of variational inequalities (VIs), with a focus on applications in management science and finance.

Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field.

The 1990 Seminar on Stochastic Processes was held at the University of British Columbia from May 10 through May 12, 1990.

Stochastic Processes: General Theory starts with the fundamental existence theorem of Kolmogorov, together with several of its extensions to stochastic processes.