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Most popular at the top
- Cambridge University Press 2004; US$ 48.00
This 2004 book introduces ways of modelling phenomena that occur over time. Covers stochastic processes, survival analysis, time series and more. more...
- World Scientific Publishing Company 2005; US$ 176.00
This 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...
- Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 139.00
Stochastic 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...
- Springer 2007; US$ 179.00
Stochastic 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...
- Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 109.00
The 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...
- Springer 2007; US$ 169.00
Provides 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...
- Springer 2007; US$ 169.00
This 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...
- Oxford University Press, UK 2008; US$ 98.99
Stochastic filtering theory is a field that has seen a rapid development in recent years and this book, aimed at graduates and researchers in applied mathematics, provides an accessible introduction covering recent developments. - ;Stochastic Filtering Theory uses probability tools to estimate unobservable stochastic processes that arise in many applied... more...
- Springer 2008; US$ 59.95
The 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...
- Springer 2009; US$ 89.99
Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, Poisson processes, and Brownian motion. This book presents structure and basic properties of these stochastic processes. more...