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.
This is an essential textbook for senior undergraduate and graduate students of statistics, stochastic processes, stochastic finance, and probability theory.
This is an essential textbook for senior undergraduate and graduate students of statistics, stochastic processes, stochastic finance, and probability theory.
This self-contained book offers an extensive state-of-the-art exposition of rotational integral geometry, a field that has reached significant maturity over the past four decades.
This self-contained book offers an extensive state-of-the-art exposition of rotational integral geometry, a field that has reached significant maturity over the past four decades.
This volume contains the contributions of the participants of the 14th ISAAC congress, held at the University of Sao Paulo, Campus Ribeirao Preto, Brazil, on July 17-21, 2023.
This book delves into the foundational principles governing the treatment of molecular networks and "e;chemical space"e;-the comprehensive domain encompassing all physically achievable molecules-from the perspectives of vector space, graph theory, and data science.
This book delves into the foundational principles governing the treatment of molecular networks and "e;chemical space"e;-the comprehensive domain encompassing all physically achievable molecules-from the perspectives of vector space, graph theory, and data science.
This book constructs input finite dimensional (FD) models that are amendable for numerical calculations and provides accurate representations for responses of dynamical systems to these inputs, i.
This book constructs input finite dimensional (FD) models that are amendable for numerical calculations and provides accurate representations for responses of dynamical systems to these inputs, i.
Introducing a groundbreaking framework for stochastic partial differential equations (SPDEs), this work presents three significant advancements over the traditional variational approach.
Introducing a groundbreaking framework for stochastic partial differential equations (SPDEs), this work presents three significant advancements over the traditional variational approach.
This book is the seventh of 15 related monographs, concerns nonlinear dynamics and singularity of cubic dynamical systems possessing a product-cubic vector field and a self-univariate quadratic vector field.
This book is the seventh of 15 related monographs, concerns nonlinear dynamics and singularity of cubic dynamical systems possessing a product-cubic vector field and a self-univariate quadratic vector field.
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference brings together contributions to this important area of research and engineering.
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference brings together contributions to this important area of research and engineering.
This thesis advances our understanding of how thermal anisotropy can be exploited to extract work through a mechanism that is quite distinct from the classical Carnot heat engine.
This thesis advances our understanding of how thermal anisotropy can be exploited to extract work through a mechanism that is quite distinct from the classical Carnot heat engine.
This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters.
This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters.
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property.
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property.
This book constitutes the refereed proceedings of the 8th International Conference on Belief Functions, BELIEF 2024, held in Belfast, UK, in September 2-4, 2024.
This book constitutes the refereed proceedings of the 8th International Conference on Belief Functions, BELIEF 2024, held in Belfast, UK, in September 2-4, 2024.
This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and multiple testing, Bernstein-von Mises theorems and variational Bayes approximations, many of which have previously only been accessible through research articles.
This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and multiple testing, Bernstein-von Mises theorems and variational Bayes approximations, many of which have previously only been accessible through research articles.
This monograph explores the interdisciplinary applications of information theory, focusing on the concepts of entropy, mutual information, and their implications in various fields.
This monograph explores the interdisciplinary applications of information theory, focusing on the concepts of entropy, mutual information, and their implications in various fields.
This book is a comprehensive guide to pseudo-Hermitian random matrices, their properties, and their role in many models that are relevant to physical processes.
This book is a comprehensive guide to pseudo-Hermitian random matrices, their properties, and their role in many models that are relevant to physical processes.
This book delves into a rigorous mathematical exploration of the well-posedness and long-time behavior of weak solutions to nonlinear Fokker-Planck equations, along with their implications in the theory of probabilistically weak solutions to McKean-Vlasov stochastic differential equations and the corresponding nonlinear Markov processes.
This book delves into a rigorous mathematical exploration of the well-posedness and long-time behavior of weak solutions to nonlinear Fokker-Planck equations, along with their implications in the theory of probabilistically weak solutions to McKean-Vlasov stochastic differential equations and the corresponding nonlinear Markov processes.
Kolmogorov equations are a fundamental bridge between the theory of partial differential equations and that of stochastic differential equations that arise in several research fields.
Kolmogorov equations are a fundamental bridge between the theory of partial differential equations and that of stochastic differential equations that arise in several research fields.
This revised book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments, and statistical quality control.
