Stochastics

This monograph presents the work of the authors in metrical theory of continued fractions in the last two decades.

Learn about the basics and the future of vehicular networking research with this essential guide to in- and inter-vehicle communication.

Now in its second edition, this book covers two major classes of mixed effects models-linear mixed models and generalized linear mixed models-and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields.

ThisresearchmonographdevelopstheHamilton-Jacobi-Bellman(HJB)theory viathedynamicprogrammingprincipleforaclassofoptimalcontrolproblems for stochastic hereditary di?

A hundred years ago it became known that deterministic systems can exhibit very complex behavior.

These notes were written as a result of my having taught a "e;nonmeasure theoretic"e; course in probability and stochastic processes a few times at the Weizmann Institute in Israel.

Introduction to Probability and Statistics for Engineers and Scientists, Third Edition, provides an introduction to applied probability and statistics for engineering or science majors .

A fascinating and instructive guide to Markov chains for experienced users and newcomers alike This unique guide to Markov chains approaches the subject along the four convergent lines of mathematics, implementation, simulation, and experimentation.

This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and multiple testing, Bernstein-von Mises theorems and variational Bayes approximations, many of which have previously only been accessible through research articles.

The Second Silivri Workshop functioned as a short summer school and a working conference, producing lecture notes and research papers on recent developments of Stochastic Analysis on Wiener space.

Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: How does a machine learn a concept on the basis of examples?

In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented.

Using everyday examples to demystify probability, this classic is now in its third edition with new chapters, exercises and examples.

Frederick Mosteller has inspired numerous statisticians and other scientists by his creative approach to statistics and its applications.

This book puts forward a new mathematical theory to study chaotic phenomenon.

Simulation, Sixth Edition continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena.

Branching processes form one of the classical fields of applied probability and are still an active area of research.

This monograph is a progressive introduction to non-commutativity in probability theory.

Fundamentals of Matrix-Analytic Methods targets advanced-level students in mathematics, engineering and computer science.

This expanded edition of the classic work on empirical processes now boasts several new proved theorems not in the first.

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.

The ultimate objective of this book is to present a panoramic view of the main stochastic processes which have an impact on applications, with complete proofs and exercises.

discussed in this book.

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.

This book provides a detailed exposition of a wide range of topics in geometric group theory, inspired by Gromov's pivotal work in the 1980s.

In this monograph we have considered a class of autoregressive models whose coefficients are random.

Introducing a groundbreaking framework for stochastic partial differential equations (SPDEs), this work presents three significant advancements over the traditional variational approach.

Interest in the his tory of statistics has grown substantially in recent years and the subject is now covered by a number of excellent books.

This book provides a compact and systematic overview of closure properties of heavy-tailed and related distributions, including closure under tail equivalence, convolution, finite mixing, maximum, minimum, convolution power and convolution roots, and product-convolution closure.

Any method of fitting equations to data may be called regression.

This book is for a first course in stochastic processes taken by undergraduates or master's students who have had a course in probability theory.

This textbook is based on a three-semester course of lectures given by the author in recent years in the Mechanics-Mathematics Faculty of Moscow State University and issued, in part, in mimeographed form under the title Probability, Statistics, Stochastic Processes, I, II by the Moscow State University Press.

This outline of statistics as an aid in decision making will introduce a reader with limited mathematical background to the most important modern statistical methods.

Game theory is the theory of social situations, and the majority of research into the topic focuses on how groups of people interact by developing formulas and algorithms to identify optimal strategies and to predict the outcome of interactions.

The stability analysis of stochastic models for telecommunication systems is an intensively studied topic.

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.

Markov processes are processes that have limited memory.

Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering.

Financial globalization has increased the significance of methods used in the evaluation of country risk, one of the major research topics in economics and finance.

This book provides a comprehensive overview of discrete mathematics, probability theory, and stochastic processes, covering a wide range of topics in each area.

This self-contained, comprehensive book tackles the principal problems and advanced questions of probability theory and random processes in 22 chapters, presented in a logical order but also suitable for dipping into.

This book originated from our interest in sea surface temperature variability.

Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences.

The purpose of this book is to provide a sound introduction to the study of real-world phenomena that possess random variation.

This book is intended as a one-semester first course in probability and statistics, requiring only a knowledge of calculus.

This book presents essential tools for modelling non-linear time series.

This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation?

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.