Stochastics

Survival analysis, the analysis of failure time data, is a rapid developing area and a number of books on the topic have been published in last twenty-five years.

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s.

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.

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images.

This book provides new insight into Markovian dependence via the cycle decompositions.

The purpose of this book is to give a detailed account of some recent devel- ments in the ?

Recent theoretical and empirical studies have concluded that in order to be accurate, poverty and deprivation must be measured within a multidimensional framework that is consistent, efficient, and statistically robust.

Ageing and dependence are two important characteristics in reliability and survival analysis, and they affect significantly the decision people make with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas.

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

Extreme Value Theory offers a careful, coherent exposition of the subject starting from the probabilistic and mathematical foundations and proceeding to the statistical theory.

The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains.

Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy.

This book arose out of two graduate courses that the authors have taught duringthepastseveralyears;the?

A classical queueing model consists of three parts - arrival process, service process, and queue discipline.

Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right.

Aims to give to the reader the tools necessary to apply semi-Markov processes in real-life problems.

Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time.

This book is devoted to the study and optimization of spatiotem- ral stochastic processes.

Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology.

This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions.

In the Leibniz-Newton calculus, one learns the di?

If people do not believe that mathematics is simple, it is only because they do not realize how complicated life is.

This book is about random objects--sequences, processes, arrays, measures, functionals--with interesting symmetry properties.

This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness.

Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more.

This book is based mainly on the lecture notes that I have been using since 1993 for a course on applied probability for engineers that I teach at the Ecole Polytechnique de Montreal.

From the reviews of the First Edition: "e;This excellent book is based on several sets of lecture notes written over a decade and has its origin in a one-semester course given by the author at the ETH, Zurich, in the spring of 1970.

Copulas are functions that join multivariate distribution functions to their one-dimensional margins.

Since the pioneering work of Black, Scholes, and Merton in the field of financial mathematics, research has led to the rapid development of a substantial body of knowledge, with plenty of applications to the common functioning of the world's financial institutions.

Most manufacturing systems are large, complex, and operate in an environment of uncertainty.

This book is a revised and expanded edition of a successful graduate and reference text.

This book integrates coverage of random/probabilistic algorithms, assertion-based program reasoning, and refinement programming models, providing a highly focused survey on probabilistic program semantics.

This book focuses on two-time-scale Markov chains in discrete time.

"e;I know it's trivial, but I have forgotten why"e;.

Services requiring parts has become a $1.

This book is aimed at postgraduate students in applied mathematics as well as at engineering and physics students with a ?

The change-point problem has attracted many statistical researchers and practitioners during the last few decades.

Theprimarybiostatisticaltoolsinmodernmedicalresearcharesingle-outcome, multiple-predictor methods: multiple linear regression for continuous o- comes, logistic regression for binary outcomes, and the Cox proportional h- ardsmodelfortime-to-eventoutcomes.

VLSI CADhas greatly bene?

Stochastic differential equations (SDEs) are a powerful tool in science, mathematics, economics and finance.

Intuitive Probability and Random Processes using MATLAB(R) is an introduction to probability and random processes that merges theory with practice.

Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field.

Peter Kall and Janos Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization.

Exploring Probability in School provides a new perspective into research on the teaching and learning of probability.

System Modeling and Optimization is an indispensable reference for anyone interested in the recent advances in these two disciplines.

Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics.

Around the world, liberalization and privatization in the electricity industry have lead to increased competition among utilities.

This text is concerned with Bayesian learning, inference and forecasting in dynamic environments.