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Stochastic processes

Most popular at the top

  • Random Walks and Geometryby Vadim Kaimanovich; Klaus Schmidt; Wolfgang Woess

    De Gruyter 2004; US$ 307.00

    Recent developments show that probability methods have become a very powerful tool in such different areas as statistical physics, dynamical systems, Riemannian geometry, group theory, harmonic analysis, graph theory and computer science. This volume is an outcome of the special semester 2001 - Random Walks held at the Schrödinger Institute in Vienna,... more...

  • Data Assimilationby Geir Evensen

    Springer 2006; US$ 135.00

    Covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. more...

  • Finite Mixture and Markov Switching Modelsby Sylvia Frühwirth-Schnatter

    Springer 2006; US$ 179.00

    The past years have seen powerful computational tools for modeling which combine a Bayesian approach with Monte simulation techniques based on Markov chains. This book reviews these techniques and covers advances in the field. It also offers a presentation of the Bayesian perspective of finite mixture modelling. more...

  • Modeling with Itô Stochastic Differential Equationsby Edward Allen

    Springer 2007; US$ 139.00

    Dynamical systems with random influences occur throughout the physical, biological, and social sciences. By carefully studying a randomly varying system over a small time interval, a discrete stochastic process model can be constructed. Next, letting the time interval shrink to zero, an Ito stochastic differential equation model for the dynamical system... more...

  • Information Criteria and Statistical Modelingby Sadanori Konishi; Genshiro Kitagawa

    Springer 2007; US$ 149.00

    The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering. One of the main objectives of this book is... more...

  • An Introduction to the Theory of Point Processes 2by D.J. Daley; David Vere-Jones

    Springer 2005; US$ 169.00

    Sets out the basic theory of random measures and point processes. This volume covers the topics of: limit theorems, ergodic theory, Palm theory, and evolutionary behaviour via martingales and conditional intensity. It also includes discussions of marked point processes, convergence to equilibrium, and the structure of spatial point processes. more...

  • Stochastic Calculus for Fractional Brownian Motion and Applicationsby Francesca Biagini; Yaozhong Hu; Bernt Oksendal; Tusheng Zhang

    Springer 2008; US$ 119.00

    Fractional Brownian motion (fBm) has been widely used to model a number of phenomena in diverse fields from biology to finance. This huge range of potential applications makes fBm an interesting object of study. fBm represents a natural one-parameter extension of classical Brownian motion therefore it is natural to ask if a stochastic calculus for... more...

  • Analytical Methods for Markov Semigroupsby Luca Lorenzi; Marcello Bertoldi

    Taylor and Francis 2006; US$ 146.95

    For the first time in book form, Analytical Methods for Markov Semigroups provides a comprehensive analysis on Markov semigroups both in spaces of bounded and continuous functions as well as in Lp spaces relevant to the invariant measure of the semigroup. Exploring specific techniques and results, the book collects and updates the literature associated... more...

  • Stochastic Ordinary and Stochastic Partial Differential Equationsby Peter Kotelenez

    Springer 2008; US$ 129.00

    This book provides the first rigorous derivation of mesoscopic and macroscopic equations from a deterministic system of microscopic equations. The microscopic equations are cast in the form of a deterministic (Newtonian) system of coupled nonlinear oscillators for N large particles and infinitely many small particles. The mesoscopic equations are stochastic... more...

  • Stochastic Learning and Optimizationby Xiren Cao

    Springer 2007; US$ 179.00

    Performance optimization is important in designing and operating modern engineering systems in many areas, including communications (Internet and wireless), manufacturing, robotics, and logistics. This book proposes research in performance optimization and looks at areas that seek to make the "best decision" to optimize system performance. more...