This book presents introductions to the essential mathematical aspects of complexity science, suitable for advanced undergraduate/masters-level students and researchers.
Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades.
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.
This volume is a collection of chapters covering the latest developments in applications of financial mathematics and statistics to topics in energy, commodity financial markets and environmental economics.
This book highlights the forefront of research on statistical distribution theory, with a focus on unconventional random quantities, and on phenomena such as random partitioning.
Potential Theory presents a clear path from calculus to classical potential theory and beyond, with the aim of moving the reader into the area of mathematical research as quickly as possible.
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory.
The papers contained in this volume are an indication of the topics th discussed and the interests of the participants of The 9 International Conference on Probability in Banach Spaces, held at Sandjberg, Denmark, August 16-21, 1993.
There is currently ever pressing need to provide a critical assessment of the current knowledge and indicate new challenges which are brought by the present time in fighting the man-made and natural hazards in transient analysis of structures.
These Lecture Notes provide an introduction to the study of those discrete surfaces which are obtained by randomly gluing polygons along their sides in a plane.
This collection of selected, revised and extended contributions resulted from a Workshop on BSDEs, SPDEs and their Applications that took place in Edinburgh, Scotland, July 2017 and included the 8th World Symposium on BSDEs.
This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales.
Filling a longstanding need in the physical sciences, Bayesian Inference offers the first basic introduction for advanced undergraduates and graduates in the physical sciences.
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations.
Fractional Brownian motion (fBm) is a stochastic process which deviates significantly from Brownian motion and semimartingales, and others classically used in probability theory.
This book organizes and explains, in a systematic and pedagogically effective manner, recent advances in path integral solution techniques with applications in stochastic engineering dynamics.
An Introduction to Measure-Theoretic Probability, Second Edition, employs a classical approach to teaching the basics of measure theoretic probability.
This volumepresents a collection of papers covering applications from a wide range ofsystems with infinitely many degrees of freedom studied using techniques fromstochastic and infinite dimensional analysis, e.
Dies ist eine Einführung in die Theorie der (Wahrscheinlichkeiten der) großen Abweichungen, die mit Hilfe analytischer Methoden die exponentielle Abfallrate sehr kleiner Wahrscheinlichkeiten charakterisiert.
As climate change continues to dominate the international environmental agenda, phenology - the study of the timing of recurring biological events - has received increasing research attention, leading to an emerging consensus that phenology can be viewed as an 'early warning system' for climate change impact.
Stochastic Processes: General Theory starts with the fundamental existence theorem of Kolmogorov, together with several of its extensions to stochastic processes.
Aufgrund einer in den letzten Jahren sprunghaft gewachsenen Verfüg barkeit über Rechnerkapazitäten, insbesondere im Bereich der Personal Computer (PC), lassen sich heute auch umfangreiche und aufwendige statistische Datenanalysen innerhalb kürzester Zeit ausführen.
Intended for advanced undergraduates and graduate students, this book is a practical guide to the use of probability and statistics in experimental physics.
This volume contains almost all of the papers that were presented at the Workshop on Stochastic Theory and Control that was held at the Univ- sity of Kansas, 18-20 October 2001.
Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist.
It was generally believed that the study of probability theory was started by Pascal and Fermat in 1654 when they succeeded in deriving the exact probabilitiesforcertaingamblingproblem.
Kiyosi Ito's greatest contribution to probability theory may be his introduction of stochastic differential equations to explain the Kolmogorov-Feller theory of Markov processes.
Main themes are complete integrability, bi-Hamiltonian structures, hierarchies, impact on string theory, links with quantum groups, random perturbations of deterministic dynamics and the onset of stochasticity/chaos/ in case of particle motion, and the relation between randomness and quantisation.
This book is devoted to the study of multivariate discrete q-distributions, which is greatly facilitated by existing multivariate q-sequences and q-functions.
