Stochastics

This book highlights the latest advances in stochastic processes, probability theory, mathematical statistics, engineering mathematics and algebraic structures, focusing on mathematical models, structures, concepts, problems and computational methods and algorithms important in modern technology, engineering and natural sciences applications.

The main purpose of the book is to give a rigorous introduction to the most important and useful solution methods of various types of stochastic control problems for jump diffusions and their applications.

This book provides an overview of the risk components of CoCo bonds.

This monograph focuses on those stochastic quickest detection tasks in disorder problems that arise in the dynamical analysis of statistical data.

This book offers a comprehensive and readable introduction to modern business and data analytics.

This book includes the texts of the survey lectures given by plenary speakers at the 11th International ISAAC Congress held in Vaxjo, Sweden, on 14-18 August, 2017.

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 book explores mathematics in a wide variety of applications, ranging from problems in electronics, energy and the environment, to mechanics and mechatronics.

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

Fractional Calculus and Fractional Processes with Applications to Financial Economics presents the theory and application of fractional calculus and fractional processes to financial data.

This book presents a concise and rigorous treatment of stochastic calculus.

This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes.

This book provides the reader with a background on simulating copulas and multivariate distributions in general.

Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks.

This graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications.

These days, an increasing amount of information can be obtained in graphical forms, such as weather maps, soil samples, locations of nests in a breeding colony, microscopical slices, satellite images, radar or medical scans and X-ray techniques.

The concept of dependence permeates the Earth and its inhabitants in a most profound manner.

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

This volume concentrates on how to construct a Markov process by starting with a suitable pseudo-differential operator.

Hermite's theorem makes it known that there are three levels of mathematical frames in which a simple addition formula is valid.

This Second Edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools.

This book investigates applications of probability theory to random events from an economic standpoint and considers how economics can deal with uncertainty in today's world.

This book investigates applications of probability theory to random events from an economic standpoint and considers how economics can deal with uncertainty in today's world.

This book undertakes a detailed construction of Dynamic Markov Bridges using a combination of theory and real-world applications to drive home important concepts and methodologies.

The book is a comprehensive, self-contained introduction to the mathematical modeling and analysis of disease transmission models.

This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems.

This book undertakes a detailed construction of Dynamic Markov Bridges using a combination of theory and real-world applications to drive home important concepts and methodologies.

This book provides a systematic and accessible approach to stochastic differential equations, backward stochastic differential equations, and their connection with partial differential equations, as well as the recent development of the fully nonlinear theory, including nonlinear expectation, second order backward stochastic differential equations, and path dependent partial differential equations.

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability.

This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them.

This book contains articles arising from a conference in honour of mathematician-statistician Mikl?

This monograph is a sequel to Brownian Motion and Stochastic Calculus by the same authors.

This volume opens the world of free probability to a wide variety of readers.

This volume presents some of the research topics discussed at the 2014-2015 Annual Thematic Program Discrete Structures: Analysis and Applications at the Institute of Mathematics and its Applications during the Spring 2015 where geometric analysis, convex geometry and concentration phenomena were the focus.

This book contains an in-depth treatment of matrix-exponential (ME) distributions and their sub-class of phase-type (PH) distributions.

Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance.

This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling.

This volume is a collection of chapters covering the latest developments in applications of financial mathematics and statistics to topics in energy, commodity financial markets and environmental economics.

This textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations.

This book provides a theoretical background of branching processes and discusses their biological applications.

This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences.

The main purpose of the book is to show how a viscosity approach can be used to tackle control problems in insurance.

The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling.

This book is comprised of selected research articles developed from a workshop on Ergodic Theory, Probabilistic Methods and Applications, held in April 2012 at the Banff International Research Station.

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory.

This volume features selected and peer-reviewed articles from the Pan-American Advanced Studies Institute (PASI).

Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research.

Quite apart from the fact that percolation theory had its orlgln in an honest applied problem (see Hammersley and Welsh (1980)), it is a source of fascinating problems of the best kind a mathematician can wish for: problems which are easy to state with a minimum of preparation, but whose solutions are (apparently) difficult and require new methods.