Stochastics

Besides a number of papers on classical areas of research in probability such as martingale theory, Malliavin calculus and 2-parameter processes, this new volume of the Séminaire de Probabilités develops the following themes: - chaos representation for some new kinds of martingales, - quantum probability, - branching aspects on Brownian excursions, - Brownian motion on a set of rays.

This handbook is a realization of a long term goal of BMDP Statistical Software.

This book contains 30 selected, refereed papers from an in-ternational conference on bootstrapping and related techni-ques held in Trier 1990.

While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting.

This book is a systematic, rigorous, and self-consistent introduction to the theory of continuous-time stochastic processes.

This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matematica Oaxaca (CMO), Mexico.

The infinite dimensional analysis as a branch of mathematical sciences was formed in the late 19th and early 20th centuries.

This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research.

This volume presents the proceedings of the meeting New Trends in One-Dimensional Dynamics, which celebrated the 70th birthday of Welington de Melo and was held at the IMPA, Rio de Janeiro, in November 2016.

The aim of this book is to present a survey of the many ways in which the statistical package GLIM may be used to model and analyze stochastic processes.

This book offers a gentle yet rigorous introduction to probability theory, with a special focus on finite probability spaces.

This book provides an introduction to dynamical systems with multiple time scales.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind.

This book is interdisciplinary and unites several areas of applied probability, statistics, and computational mathematics including computer experiments, optimal experimental design, and global optimization.

These Lecture Notes provide an introduction to the study of those discrete surfaces which are obtained by randomly gluing polygons along their sides in a plane.

In 1991, a subcommittee of the Federal Committee on Statistical Methodology met to document the use of indirect estimators - that is, estimators which use data drawn from a domain or time different from the domain or time for which an estimate is required.

This textbook is devoted to the general asymptotic theory of statistical experiments.

The following topical subjects were discussed: quantum stochastic calculus; unbounded quantum dynamical system; the principles of nonstandard analysis that are fundamental to an understanding of a modern approach to stochastic analysis on fractals; Brownian motion on nested fractals; stable processes; stochastic modelling of sexually transmitted diseases.

Author's Note: The material of this book has been reworked and expanded with a lot more detail and published in the author's 2014 book "e;Upper and Lower Bounds for Stochastic Processes"e; (Ergebnisse Vol.

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Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios.

This book summarizes the developments in stochastic analysis and estimation.

Many mathematical assumptions on which classical derivative pricing methods are based have come under scrutiny in recent years.

Model Validation and Uncertainty Quantification, Volume 3:  Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference brings together contributions to this important area of research and engineering.

Reliability theory and applications become major concerns of engineers and managers engaged in making high quality products and designing highly reliable systems.

The most recent methods in various branches of lattice path and enumerative combinatorics along with relevant applications are nicely grouped together and represented in this research contributed volume.

This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting.

This book explores various renewal processes in the context of probability theory, uncertainty theory and chance theory.

This volume presents the lecture notes from two courses given by Davar Khoshnevisan and Rene Schilling, respectively, at the second Barcelona Summer School on Stochastic Analysis.

Services requiring parts has become a $1.

The contents of this monograph approximate the lectures I gave In a graduate course at Stanford University in the first half of 1981.

A bibliography on stochastic orderings.

Discrete stochastic models are tools that allow us to understand, control, and optimize engineering systems and processes.

This book includes a review of mathematical tools like modelling, analysis of stochastic processes, calculus of variations and stochastic differential equations which are applied to solve financial problems like modern portfolio theory and option pricing.

This book discusses the systems of interacting particles evolving in the random media.

This thesis explores several interdisciplinary topics at the border of theoretical physics and biology, presenting results that demonstrate the power of methods from statistical physics when applied to neighbouring disciplines.

Addressed to both pure and applied probabilitists, including graduate students, this text is a pedagogically-oriented introduction to the Schwartz-Meyer second-order geometry and its use in stochastic calculus.

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.

Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or absolutely regular.

Rolf Steyer, Autor des erfolgreichen Lehrbuchs "Messen und Testen", schließt mit diesem Buch die Kluft zwischen Regressionstheorie und deren empirischer Anwendung, der Regressionsanalyse.