The Elements of Stochastic Processes with Applications to the Natural Sciences

The Elements of Stochastic Processes with Applications to the Natural Sciences
Author: Norman T. J. Bailey
Publisher: John Wiley & Sons
Total Pages: 272
Release: 1964
Genre: Mathematics
ISBN:

Recurrent events; Random walk models; Markov chains; Discrete branching processes; Markov processes in continuous time; Homogeneous birth and death processes; Some non-homogeneous processes; Multi-dimensional processes; Queueing processes; Epidemic processes; Competition and predation; Diffusion processes; Approximations to stochastic processes; Some non-markovian processes.

Stochastic processes with applications in the natural sciences

Stochastic processes with applications in the natural sciences
Author: Kulik, Alexei
Publisher: Universitätsverlag Potsdam
Total Pages: 138
Release: 2017
Genre: Mathematics
ISBN: 3869564148

The interdisciplinary workshop STOCHASTIC PROCESSES WITH APPLICATIONS IN THE NATURAL SCIENCES was held in Bogotá, at Universidad de los Andes from December 5 to December 9, 2016. It brought together researchers from Colombia, Germany, France, Italy, Ukraine, who communicated recent progress in the mathematical research related to stochastic processes with application in biophysics. The present volume collects three of the four courses held at this meeting by Angelo Valleriani, Sylvie Rœlly and Alexei Kulik. A particular aim of this collection is to inspire young scientists in setting up research goals within the wide scope of fields represented in this volume.

Stochastic Processes and Applications

Stochastic Processes and Applications
Author: Grigorios A. Pavliotis
Publisher: Springer
Total Pages: 345
Release: 2014-11-19
Genre: Mathematics
ISBN: 1493913239

This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.

Stochastic Processes, Statistical Methods, and Engineering Mathematics

Stochastic Processes, Statistical Methods, and Engineering Mathematics
Author: Anatoliy Malyarenko
Publisher: Springer Nature
Total Pages: 907
Release: 2023-01-26
Genre: Mathematics
ISBN: 3031178203

The goal of the 2019 conference on Stochastic Processes and Algebraic Structures held in SPAS2019, Västerås, Sweden, from September 30th to October 2nd 2019, was to showcase the frontiers of research in several important areas of mathematics, mathematical statistics, and its applications. The conference was organized around the following topics 1. Stochastic processes and modern statistical methods,2. Engineering mathematics,3. Algebraic structures and their applications. The conference brought together a select group of scientists, researchers, and practitioners from the industry who are actively contributing to the theory and applications of stochastic, and algebraic structures, methods, and models. The conference provided early stage researchers with the opportunity to learn from leaders in the field, to present their research, as well as to establish valuable research contacts in order to initiate collaborations in Sweden and abroad. New methods for pricing sophisticated financial derivatives, limit theorems for stochastic processes, advanced methods for statistical analysis of financial data, and modern computational methods in various areas of applied science can be found in this book. The principal reason for the growing interest in these questions comes from the fact that we are living in an extremely rapidly changing and challenging environment. This requires the quick introduction of new methods, coming from different areas of applied science. Advanced concepts in the book are illustrated in simple form with the help of tables and figures. Most of the papers are self-contained, and thus ideally suitable for self-study. Solutions to sophisticated problems located at the intersection of various theoretical and applied areas of the natural sciences are presented in these proceedings.

The Elements of Stochastic Processes with Applications to the Natural Sciences

The Elements of Stochastic Processes with Applications to the Natural Sciences
Author: Norman T. J. Bailey
Publisher: John Wiley & Sons
Total Pages: 268
Release: 1991-01-16
Genre: Mathematics
ISBN: 9780471523680

Develops an introductory and relatively simple account of the theory and application of the evolutionary type of stochastic process. Professor Bailey adopts the heuristic approach of applied mathematics and develops both theoretical principles and applied techniques simultaneously.

Stochastic Models, Statistics and Their Applications

Stochastic Models, Statistics and Their Applications
Author: Ansgar Steland
Publisher: Springer Nature
Total Pages: 450
Release: 2019-10-15
Genre: Mathematics
ISBN: 3030286657

This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.