Stochastics

This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems.

This book offers a detailed review of perturbed random walks, perpetuities, and random processes with immigration.

This book offers an introduction to the theory of non-autonomous and stochastic dynamical systems, with a focus on the importance of the theory in the Applied Sciences.

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models.

The present volume develops the theory of integration in Banach spaces, martingales and UMD spaces, and culminates in a treatment of the Hilbert transform, Littlewood-Paley theory and the vector-valued Mihlin multiplier theorem.

This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes.

This text develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications.

This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization.

The classical theory of random walks describes the asymptotic behavior of sums of independent identically distributed random real variables.

This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals.

This brief treats dynamical systems that involve delays and random disturbances.

This volume consists of papers inspired by the special session on pseudo-differential operators at the 10th ISAAC Congress held at the University of Macau, August 3-8, 2015 and the mini-symposium on pseudo-differential operators in industries and technologies at the 8th ICIAM held at the National Convention Center in Beijing, August 10-14, 2015.

This is a unique volume by a unique scientist, which combines conceptual, formal, and engineering approaches in a way that is rarely seen.

The canonical way to establish the central limit theorem for i.

Focusing on p-adic and adelic analogues of pseudodifferential equations, this monograph presents a very general theory of parabolic-type equations and their Markov processes motivated by their connection with models of complex hierarchic systems.

This Festschrift resulted from a workshop on "e;Advanced Modelling in Mathematical Finance"e; held in honour of Ernst Eberlein's 70th birthday, from 20 to 22 May 2015 in Kiel, Germany.

This research monograph brings together, for the first time, the varied literature on Yosida approximations of stochastic differential equations (SDEs) in infinite dimensions and their applications into a single cohesive work.

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory.

This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory).

This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria.

As in the previous Seminar Notes, the current volume reflects general trends in the study of Geometric Aspects of Functional Analysis, understood in a broad sense.

This book constitutes the refereed proceedings of the 15th International Scientific Conference on Information Technologies and Mathematical Modeling, named after A.

In addition to its further exploration of the subject of peacocks, introduced in recent Seminaires de Probabilites, this volume continues the series' focus on current research themes in traditional topics such as stochastic calculus, filtrations and random matrices.

This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response.

This first text on the subject provides a comprehensive introduction to the representation theory of finite monoids.

The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text.

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL).

This focuses on the developing field of building probability models with the power of symbolic algebra systems.

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy).

This book highlights the latest advances in engineering mathematics with a main focus on the mathematical models, structures, concepts, problems and computational methods and algorithms most relevant for applications in modern technologies and engineering.

This book highlights the latest advances in engineering mathematics with a main focus on the mathematical models, structures, concepts, problems and computational methods and algorithms most relevant for applications in modern technologies and engineering.

This book collects lectures given by the plenary speakers at the 10th International ISAAC Congress, held in Macau, China in 2015.

This volume presents classical results of the theory of enlargement of filtration.

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.

This new edition offers a comprehensive introduction to the analysis of data using Bayes rule.

Offering the first comprehensive treatment of the theory of random measures, this book has a very broad scope, ranging from basic properties of Poisson and related processes to the modern theories of convergence, stationarity, Palm measures, conditioning, and compensation.

This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France.

Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup.

The contributions by epidemic modeling experts describe how mathematical models and statistical forecasting are created to capture the most important aspects of an emerging epidemic.

This brief broadens readers' understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS).

This monograph deals with the mathematics of extending given partial data-sets obtained from experiments; Experimentalists frequently gather spectral data when the observed data is limited, e.

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science.

This book covers the theory of derivatives pricing and hedging as well as techniques used in mathematical finance.

This is a self-contained exposition by one of the leading experts in lattice theory, George Gratzer, presenting the major results of the last 70 years on congruence lattices of finite lattices, featuring the author's signature Proof-by-Picture method.

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.

This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function.

This monograph aims to promote original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries.

This is a comprehensive survey on the research on the parabolic Anderson model - the heat equation with random potential or the random walk in random potential - of the years 1990 - 2015.

This book elaborates on the asymptotic behaviour, when N is large, of certain N-dimensional integrals which typically occur in random matrices, or in 1+1 dimensional quantum integrable models solvable by the quantum separation of variables.

In this volume a theory for models of transport in the presence of a free boundary is developed.