Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models.
The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies.
Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models.
Clustering and Classification, Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of statistics, mathematics, computer science and artificial intelligence.
This book constitutes the refereed proceedings of the 5th International Symposium on Stochastic Algorithms, Foundations and Applications, SAGA 2009, held in Sapporo, Japan, in October 2009.
This book presents the refereed proceedings of the Seventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, held in Ulm, Germany, in August 2006.
This book offers an in-depth review of kinetically constrained models (KCMs), a topic that lies at the crossroads of probability and statistical mechanics.
This book offers an in-depth review of kinetically constrained models (KCMs), a topic that lies at the crossroads of probability and statistical mechanics.
The idea of writing up a book on the hydrodynamic behavior of interacting particle systems was born after a series of lectures Claude Kipnis gave at the University of Paris 7 in the spring of 1988.
This is the second volume in a subseries of the Lecture Notes in Mathematics called Levy Matters, which is published at irregular intervals over the years.
This book provides a comprehensive examination of the structure of approximate optimal policies in Markov decision processes (MDPs) with finite state spaces, as well as approximate optimal solutions for deterministic discrete-time optimal control problems.
This book provides a comprehensive examination of the structure of approximate optimal policies in Markov decision processes (MDPs) with finite state spaces, as well as approximate optimal solutions for deterministic discrete-time optimal control problems.
This book addresses the well-known capability and flexibility of classical and constructive semigroups (inherited from algebraic structures), to model, solve problems in extremely diverse situations, and develop interesting new algebraic ideas with many applications and connections to other areas of mathematics (logic, biomathematics, analysis, geometry, etc.
This book addresses the well-known capability and flexibility of classical and constructive semigroups (inherited from algebraic structures), to model, solve problems in extremely diverse situations, and develop interesting new algebraic ideas with many applications and connections to other areas of mathematics (logic, biomathematics, analysis, geometry, etc.
This monograph provides a comprehensive overview of locally perturbed random walks, tools used for their analysis, and current research on their applications.
This monograph provides a comprehensive overview of locally perturbed random walks, tools used for their analysis, and current research on their applications.
This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning.
This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning.
In today's manufacturing environment, managing inventories is one of the basic concerns of enterprises dealing with materials according to their activities.
This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling problems within quantitative finance.
