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Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduce...Savoir plus
Since the seminal work of P. Anderson in 1958, localization in disordered systems has been the object of intense investigations. Mathematically speaki...Savoir plus
In this book, a beautiful interplay between probability theory (Markov processes, martingale theory) on the one hand and operator and spectral theory ...Savoir plus
Since its introduction in 1972, Stein's method has offered a completely novel way of evaluating the quality of normal approximations. Through its char...Savoir plus
This is the second volume of the reworked second edition of a key work on Point Process Theory. Fully revised and updated by the authors who have rewo...Savoir plus
Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications...Savoir plus
The author describes the current state of the art in the theory of invariant random fields. This theory is based on several different areas of mathema...Savoir plus
Gives a rigorous yet understandable presentation of the theory of stochastic processes Presents the theory of distributions of functionals of diffusio...Savoir plus
This book presents a large variety of extensions of the methods of inclusion and exclusion. Both methods for generating and methods for proof of such ...Savoir plus
This book studies the foundations of the theory of linear and nonlinear forms in single and multiple random variables including the single and multipl...Savoir plus
Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied ...Savoir plus
Introduction Deterministic Slow-Fast Systems One-Dimensional Slowly Time-Dependent Systems Stochastic Resonance Multi-Dimensional Slow-Fast Systems Ap...Savoir plus
This book is based on research that, to a large extent, started around 1990, when a research project on fluid flow in stochastic reservoirs was initia...Savoir plus
It has been widely recognized nowadays the importance of introducing mathematical models that take into account possible sudden changes in the dynamic...Savoir plus
The first comprehensive account of the theory of mass transportation problems and its applications. In Volume I, the authors systematically develop th...Savoir plus
Markov Jump Linear Systems.- Background Material.- On Stability.- Optimal Control.- Filtering.- Quadratic Optimal Control with Partial Information.- H...Savoir plus
About the first edition: To sum it up, one can perhaps see a distinction among advanced probability books into those which are original and path-break...Savoir plus
Stochastic Differential Equations have become increasingly important in modelling complex systems in physics, chemistry, biology, climatology and othe...Savoir plus
The first comprehensive account of the theory of mass transportation problems and its applications. In Volume I, the authors systematically develop th...Savoir plus
A hundred years ago it became known that deterministic systems can exhibit very complex behavior. By proving that ordinary differential equations can ...Savoir plus
This book offers a detailed review of perturbed random walks, perpetuities, and random processes with immigration. Being of major importance in modern...Savoir plus
The systematic study of existence, uniqueness, and properties of solutions to stochastic differential equations in infinite dimensions arising from pr...Savoir plus
Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied ...Savoir plus
Main concepts of quasi-stationary distributions (QSDs) for killed processes are the focus of the present volume. For diffusions, the killing is at the...Savoir plus