Stochastics

The Theory and Practice of Revenue Management is a book that comprehensively covers theory and practice of the entire field, including both quantity and price-based RM, as well as significant coverage of supporting topics such as forecasting and economics.

Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques.

This book focuses on recent advances, approaches, theories and applications related to mixture models.

This fourth edition contains several additions.

Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends.

Theory of Markov Processes provides information pertinent to the logical foundations of the theory of Markov random processes.

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

Point processes and random measures find wide applicability in telecommunications, earthquakes, image analysis, spatial point patterns, and stereology, to name but a few areas.

This book presents selected peer-reviewed contributions from the International Conference on Time Series and Forecasting, ITISE 2018, held in Granada, Spain, on September 19-21, 2018.

This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields.

Europe witnessed in the last years a number of significant power contingencies.

Provides graduate students and practitioners in physics and economics with a better understanding of stochastic processes.

From 1972 to 1974, I was working on a PhD thesis entitled Multiple Server Queues with Service Time Depending on Waiting Time.

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Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems.

Nonlinear Stochastic Processes addresses the frequently-encountered problem of incomplete information.

This SpringerBrief deals with a class of discrete-time zero-sum Markov games with Borel state and action spaces, and possibly unbounded payoffs, under discounted and average criteria, whose state process evolves according to a stochastic difference equation.

Stochastic Limit Theory, published in 1994, has become a standard reference in its field.

Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians.

This book gives a mathematical insight--including intermediate derivation steps--into engineering physics and turbulence modeling related to an anisotropic modification to the Boussinesq hypothesis (deformation theory) coupled with the similarity theory of velocity fluctuations.

This text contains ample material for a one term precalculus introduction to probability theory.

Probability and Random Processes provides a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course.

This book is the result of lectures which I gave dur- ing the academic year 1972-73 to third-year students a~ Aarhus University in Denmark.

This book presents the proceedings of the international conference Particle Systems and Partial Differential Equations X, which was held at the University of Minho, Braga, Portugal, from 2022.

Stochastic Analysis and Diffusion Processes presents a simple, mathematical introduction to Stochastic Calculus and its applications.

Our basic question is: Given a collection of DNA sequences, what underlying forces are responsible for the observed patterns of variability?

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.

In the mathematical treatment of many problems which arise in physics, economics, engineering, management, etc.

Efficient and equitable policies for managing disaster risks and adapting to global environmental change are critically dependent on development of robust options supported by integrated modeling.

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

Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math- ematics.

This monograph isdevoted to a special area ofBanach space theory-the Kothe- Bochner function space.

An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences.

Increasingly, neural networks are used and implemented in a wide range of fields and have become useful tools in probabilistic analysis and prediction theory.

This book is devoted to unstable solutions of stochastic differential equations (SDEs).

Hawkes processes are studied and used in a wide range of disciplines: mathematics, social sciences, and earthquake modelling, to name a few.

This book is a concise presentation of the normal distribution on the real line and its counterparts on more abstract spaces, which we shall call the Gaussian distributions.

Assuming only calculus and linear algebra, this book introduces the reader in a technically complete way to measure theory and probability, discrete martingales, and weak convergence.

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent.

This book is designed to provide beginning graduate stu- dents and advanced undergraduates with a rigorous and accessible foundation in the principles of probability and mathematical statistics underlying statis- tical inference in the fields of business and economics.

It was none other than Henri Poincare who at the turn of the last century, recognised that initial-value sensitivity is a fundamental source of random- ness.

The volume includes a collection of peer-reviewed contributions from among those presented at the main conference organized yearly by the Mexican Statistical Association (AME) and every two years by a Latin-American Confederation of Statistical Societies.

Highlighting the latest advances in stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020.

Comprehensive monograph by two leading international experts; includes applications to statistical and fluid mechanics and to finance.

This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems.

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

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