Stochastics

The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability.

The work consists of two introductory courses, developing different points of view on the study of the asymptotic behaviour of the geodesic flow, namely: the probabilistic approach via martingales and mixing (by Stephane Le Borgne); the semi-classical approach, by operator theory and resonances (by Frederic Faure and Masato Tsujii).

Analysis, assessment, and data management are core competencies for operation research analysts.

This is the first work on Discrepancy Theory to show the present variety of points of view and applications covering the areas Classical and Geometric Discrepancy Theory, Combinatorial Discrepancy Theory and Applications and Constructions.

Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics.

This book gives an overview of affine diffusions, from Ornstein-Uhlenbeck processes to Wishart processes and it considers some related diffusions such as Wright-Fisher processes.

These lecture notes provide an introduction to the applications of Brownian motion to analysis and more generally, connections between Brownian motion and analysis.

This is a unique book addressing the integration of risk methodology from various fields.

A certain curious feature of random objects, introduced by the author as "e;super concentration,"e; and two related topics, "e;chaos"e; and "e;multiple valleys,"e; are highlighted in this book.

This volume presents an extensive overview of all major modern trends in applications of probability and stochastic analysis.

In these lecture notes, we will analyze the behavior of random walk on disordered media by means of both probabilistic and analytic methods, and will study the scaling limits.

This volume presents recent developments in the area of Levy-type processes and more general stochastic processes that behave locally like a Levy process.

The goal of this Lecture Note is to prove a new type of limit theorems for normalized sums of strongly dependent random variables that play an important role in probability theory or in statistical physics.

These lecture notes study the interplay between randomness and geometry of graphs.

Motivated by the many and long-standing contributions of H.

In this book we analyze the error caused by numerical schemes for the approximation of semilinear stochastic evolution equations (SEEq) in a Hilbert space-valued setting.

This book constructs a rigorous framework for analysing selected phenomena in evolutionary theory of populations arising due to the combined effects of migration, selection and mutation in a spatial stochastic population model, namely the evolution towards fitter and fitter types through punctuated equilibria.

This monograph provides a self-contained and easy-to-read introduction to non-commutative multiple-valued logic algebras; a subject which has attracted much interest in the past few years because of its impact on information science, artificial intelligence and other subjects.

This monograph discusses the existence and regularity properties of local times associated to a continuous semimartingale, as well as excursion theory for Brownian paths.

The model investigated in this work, a particular cellular automaton with stochastic evolution, was introduced as the simplest case of self-organized-criticality, that is, a dynamical system which shows algebraic long-range correlations without any tuning of parameters.

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Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades.

This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility.

Traditional procedures in the statistical forecasting of time series, which are proved to be optimal under the hypothetical model, are often not robust under relatively small distortions (misspecification, outliers, missing values, etc.

This work considers a small random perturbation of alpha-stable jump type nonlinear reaction-diffusion equations with Dirichlet boundary conditions over an interval.

This thesis presents a new method for following evolving interactions between coupled oscillatory systems of the kind that abound in nature.

The book collects over 120 exercises on different subjects of Mathematical Finance, including Option Pricing, Risk Theory, and Interest Rate Models.

The series of advanced courses initiated in Seminaire de Probabilites XXXIII continues with a course by Ivan Nourdin on Gaussian approximations using Malliavin calculus.

The present volume is an extensive monograph on the analytic and geometric aspects of Markov diffusion operators.

Stability conditions for functional differential equations can be obtained using Lyapunov functionals.

This book is an introduction into stochastic processes for physicists, biologists and financial analysts.

Nonstandard Analysis enhances mathematical reasoning by introducing new ways of expression and deduction.

Soils and rocks are among the most variable of all engineering materials, and as such are highly amenable to a probabilistic treatment.

This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease expense in corrective measures.

An Introduction to Probability and Statistical Inference, Third Edition, guides the reader through probability models and statistical methods to develop critical-thinking skills.

This book discusses supply chain management, focusing on developments within modelling the dynamic behaviour of the supply chain.

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians-a textbook for courses in probability for students in mathematical statistics.

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models.

This volume gathers selected peer-reviewed papers presented at the XXVI International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), held on July 8-11, 2020 in Rio de Janeiro, Brazil.

This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability.

This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability.

This book grew out of the Random Transformations and Invariance in Stochastic Dynamics conference held in Verona from the 25th to the 28th of March 2019 in honour of Sergio Albeverio.

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Levy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes.

This book bridges the gap between theory and applications that currently exist in undergraduate engineering probability textbooks.

This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability.

The purpose of this monograph is to provide a theory of Markov processes that are invariant under the actions of Lie groups, focusing on ways to represent such processes in the spirit of the classical Levy-Khinchin representation.