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#### Inference in Hidden Markov Models

Springer-Verlag New York Inc 2006; US$ 199.00Gives a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. This book is aimed at anybody with an interest in inference for stochastic processes, researchers, and practitioners in areas such as statistics, signal processing, communications engineering, finance, and more. more...

#### Stochastic Systems In Merging Phase Space

World Scientific Publishing Company 2005; US$ 176.00This book provides recent results on the stochastic approximation of systems by weak convergence techniques. General and particular schemes of proofs for average, diffusion, and Poisson approximations of stochastic systems are presented, allowing one to simplify complex systems and obtain numerically tractable models. The systems discussed in the book... more...

#### The Malliavin Calculus and Related Topics

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 109.00The Malliavin calculus is an infinite-dimensional differential calculus on a Gaussian space. This monograph presents the main features of the Malliavin calculus and discusses its main applications. It includes applications of the Malliavin calculus in finance and a chapter on stochastic calculus with respect to the fractional Brownian motion. more...

#### Stochastic Numerics for the Boltzmann Equation

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 139.00Stochastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC) procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment... more...

#### Stochastic Switching Systems

Springer 2007; US$ 179.00Stochastic switching systems represent an interesting class of systems that can be used to model a variety of systems having abrupt random changes in their dynamics. This work presents stochastic switching systems and provides methods and techniques for the analysis and design of various control systems with or without uncertainties. more...

#### Cycle Representations of Markov Processes

Springer 2007; US$ 169.00Provides fresh insight into Markovian dependence via the cycle decompositions. This book presents an account of a class of stochastic processes known as cycle processes. It reveals interpretations of cycle representations such as homologic decompositions, orthogonality equations, Fourier series, semigroup equations, and disintegration of measures. more...

#### Introduction to Empirical Processes and Semiparametric Inference

Springer 2007; US$ 169.00This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians,... more...

#### Quasi-Stationary Phenomena in Nonlinearly Perturbed Stochastic Systems

De Gruyter 2008; US$ 238.00This book is devoted to the mathematical studies of stochastic systems with quasi-stationary phenomena which have applications to population dynamics or epidemic models. In addition to its use for the research and reference purposes, the book can also be used in special courses on the subject and as a complementary reading in general courses... more...

#### Markov Processes and Applications

Wiley 2008; US$ 96.00“Well-written, this book is suitable as a textbook for teaching a postgraduate course on applied Markov processes.” ( Mathmatical Assoc of America , June 2009) "It does provide a good introduction to each of the five application areas." ( Mathematical Reviews, July 2010) more...

#### Fundamentals of Stochastic Filtering

Springer 2008; US$ 59.95The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment... more...