Stochastics

A readable 2006 synthesis of three main areas in the modern theory of stochastic processes.

This 2004 book introduces ways of modelling phenomena that occur over time.

Graduate text decsribing two of the main tools for modern mathematical finance.

Covers an area at intersection of probability theory and statistical mechanics.

Monograph on Graph Directed Markov Systems with backgound and research level material.

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments.

* Unique in its survey of the range of topics.

The field of applied probability has changed profoundly in the past twenty years.

Claims reserving is central to the insurance industry.

This book is an introductory guide to using L vy processes for credit risk modelling.

"e;This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications.

This book is an introductory guide to using L vy processes for credit risk modelling.

A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications.

This title considers the special of random processes known as semi-Markov processes.

Switching processes, invented by the author in 1977, is the main tool used in the investigation of traffic problems from automotive to telecommunications.

This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences.

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.

The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences.

A path-breaking account of Markov decision processes-theory and computation This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates.

A unique, integrated treatment of computer modeling and simulation "e;The future of science belongs to those willing to make the shift to simulation-based modeling,"e; predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style.

Uniquely combining theory, application, and computing, this bookexplores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary)processes has become increasingly popular in a range of researchareas such as meteorology, climate, communications, economics, andmachine diagnostics.

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.

Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others.

Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more.

Despite advances in the field of geotechnical earthquake engineering, earthquakes continue to cause loss of life and property in one part of the world or another.

In many branches of science relevant observations are taken sequentially over time.

In many branches of science relevant observations are taken sequentially over time.

It is well-known that modern stochastic calculus has been exhaustively developed under usual conditions.

It is well-known that modern stochastic calculus has been exhaustively developed under usual conditions.

This book covers major measure theory topics with a fairly extensive study of their applications to probability and analysis.

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods.

The idea for this book came from the time the authors spent at the Statistics and Applied Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina starting in fall 2003.

Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing.

There has been dramatic growth in the development and application of Bayesian inference in statistics.

Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more.

This book offers an exploration of the relationships between epistemology and probability in the work of Niels Bohr, Werner Heisenberg, and Erwin Schro- * dinger, and in quantum mechanics and in modern physics as a whole.

As more applications are found, interest in Hidden Markov Models continues to grow.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

The present volume is a collective monograph devoted to applications of the optimal design theory in optimization and statistics.

This book is an evolution from my book A First Course in Information Theory published in 2002 when network coding was still at its infancy.

The Subject A little explanation is in order for our choice of the title Linear Opti- 1 mization (and corresponding terminology) for what has traditionally been called Linear Programming.

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics.

From Combinatorics to Philosophy: The Legacy of G.

This book gives you a step-by-step introduction to analysing time series using the open source software R.

This text is an introduction to the modern theory and applications of probability and stochastics.