Stochastics

This book covers numerical methods for stochastic partial differential equations with white noise using the framework of Wong-Zakai approximation.

Stochastic Limit Theory, published in 1994, has become a standard reference in its field.

Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics.

This book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions.

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Polymers occur in many different states and their physical properties are strongly correlated with their conformations.

Probabilistic analysis is increasing in popularity and importance within engineering and the applied sciences.

This book is devoted to a number of stochastic models that display scale invariance.

Three series of lectures were given at the 32nd Probability Summer School in Saint-Flour (July 7-24, 2002), by the Professors Pitman, Tsirelson and Werner.

This book introduces key results essential for financial practitioners by means of concrete examples and a fully rigorous exposition.

This new edition of the well established text Scheduling - Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world.

In this contribution, several probabilistic tools to study population dynamics are developed.

This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution.

Am Entstehen dieses Buches waren verschiedene Personen beteiligt, denen wir an dieser Stelle danken.

This is the first half of a text for a two semester course in mathematical statistics at the senior/graduate level for those who need a strong background in statistics as an essential tool in their career.

This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty.

An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used.

This book offers a gentle yet rigorous introduction to probability theory, with a special focus on finite probability spaces.

The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors.

Most probability problems involve random variables indexed by space and/or time.

Probability theory is a rapidly expanding field and is used in many areas of science and technology.

This book gives a comprehensive review of results for associated sequences and demimartingales developed so far, with special emphasis on demimartingales and related processes.

This volume comprises selected, revised papers from the Joint CIM-WIAS Workshop, TAAO 2017, held in Lisbon, Portugal, in December 2017.

This proceedings volume gathers selected, peer-reviewed papers presented at the 41st International Conference on Infinite Dimensional Analysis, Quantum Probability and Related Topics (QP41) that was virtually held at the United Arab Emirates University (UAEU) in Al Ain, Abu Dhabi, from March 28th to April 1st, 2021.

A careful and accessible exposition of functional analytic methods in stochastic analysis is provided in this book.

This book represents the refereed proceedings of the Third International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at Claremont Graduate University in 1998.

This book contains the lectures given at the Conference on Dynamics and Randomness held at the Centro de Modelamiento Matematico of the Universidad de Chile from December 11th to 15th, 2000.

This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems.

Im Gegensatz zur klassischen Theorie werden in diesem Buch Signale durch Zufallsprozesse modelliert.

Stochastic portfolio theory is a mathematical methodology for constructing stock portfolios and for analyzing the effects induced on the behavior of these portfolios by changes in the distribution of capital in the market.

This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections.

Random processes are one of the most powerful tools in the study and understanding of countless phenomena in natural and social sciences.

The Statistical Analysis of Discrete Data provides an introduction to cur- rent statistical methods for analyzing discrete response data.

In applications, and especially in mathematical finance, random time-dependent events are often modeled as stochastic processes.

These are the proceedings of the Third Max Born Symposium which took place at SobOtka Castle in September 1993.

Optimization of Stochastic Systems

The Applied and Numerical Harmonic Analysis (ANHA) book series aims to provide the engineering, mathematical, and scienti?

Stochastic differential equations, and Hoermander form representations of diffusion operators, can determine a linear connection associated to the underlying (sub)-Riemannian structure.

This is a development of the book entitled Multidimensional Second Order Stochastic Processes.

This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB).

This authored monograph presents a mathematical description of the time evolution of neutral genomic regions in terms of the differential Lyapunov equation.

This text develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications.

Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data.

Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers.

Although several books or monographs on multiobjective optimization under uncertainty have been published, there seems to be no book which starts with an introductory chapter of linear programming and is designed to incorporate both fuzziness and randomness into multiobjective programming in a unified way.

This book is a text at the introductory graduate level, for use in the one- semester or two-quarter probability course for first-year graduate students that seems ubiquitous in departments of statistics, biostatistics, mathemat- ical sciences, applied mathematics and mathematics.

My goal in writing this book has been to provide teachers and students of multi- variate statistics with a unified treatment ofboth theoretical and practical aspects of this fascinating area.