The original contributions on Bayesian econometrics gathered in this book pay tribute to Sune Karlsson, celebrating his significant work in time series econometrics and its applications in macroeconomics and finance.
The original contributions on Bayesian econometrics gathered in this book pay tribute to Sune Karlsson, celebrating his significant work in time series econometrics and its applications in macroeconomics and finance.
This book examines the symbiotic interplay between fully nonlinear elliptic partial differential equations and general potential theories of second order.
This book is an essential guide for anyone in engineering or mathematical physics looking to master the fundamental concepts of differential equations and special functions, which are crucial for solving real-world problems.
This book focuses on the crucial theme of modern test development and analysis, specifically focusing on bridging the gap between theoretical frameworks and practical applications.
In clinical trials, monitoring accumulating data at regular intervals is essential for balancing ethical and financial considerations against scientific rigor.
Wrangle stats as you learn how to graph, analyze, and interpret data with Python Statistical Analysis with Python For Dummies introduces you to the tool of choice for digging deep into data to inform business decisions.
This book is a vital resource for anyone looking to understand the essential role of graph theory as the unifying thread that connects and provides innovative solutions across a wide spectrum of modern computer science disciplines.
System dependability is a complex task to grasp and analyze since it encompasses reliability, maintainability, availability, failure mode analysis and feared events.
Graph minor theory is one of the most influential and well-developed areas of graph theory, yet its key results, particularly the work of Robertson and Seymour, have remained scattered across numerous technical papers.
The present volume collects extended abstracts of lectures and talks presented at the Summer School and Conference "e;Analysis, PDEs and Applications"e; held 24 June - 6 July 2024 at Yerevan State University, Armenia.
This book examines the symbiotic interplay between fully nonlinear elliptic partial differential equations and general potential theories of second order.
This book provides an overview of agent-based modeling (ABM) and multi-agent systems (MAS), emphasizing their significance in understanding complex economic systems, with a special focus on the emerging properties of heterogeneous agents that cannot be deduced from the characteristics of individual agents.
This book provides an overview of agent-based modeling (ABM) and multi-agent systems (MAS), emphasizing their significance in understanding complex economic systems, with a special focus on the emerging properties of heterogeneous agents that cannot be deduced from the characteristics of individual agents.
This book collects the groundbreaking research presented at the plenary lectures of the First Brazil-Portugal Joint Meeting in Mathematics, held in Salvador, Brazil, from August 14 to 20, 2022.
This book collects the groundbreaking research presented at the plenary lectures of the First Brazil-Portugal Joint Meeting in Mathematics, held in Salvador, Brazil, from August 14 to 20, 2022.
This book collects some contributions presented in the annual Congress "e;Mathematical Modeling & Human Behavior"e;, held from 10 to 12 July 2024 at Universitat Politècnica de València, Valencia, Spain.
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "e;Augmented Gaussian Process"e; methodology.
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 proceedings volume features a selection of peer-reviewed papers presented at the 6th AMMCS-International Conference on Applied Mathematics, Modeling, and Computational Science, held in Waterloo, Canada, from August 14-18, 2023.
This advanced introductory textbook offers a comprehensive approach to non-relativistic Quantum Mechanics, focusing on exact methods and mathematical techniques often overlooked in standard textbooks.
Among several main formulations, the book treats inverse problems with single measurements by Carleman estimates and describes a method for proving the uniqueness and the stability for the first-order transport equations, parabolic equations, and hyperbolic equations.
The present volume collects extended abstracts of lectures and talks presented at the Summer School and Conference "e;Analysis, PDEs and Applications"e; held 24 June - 6 July 2024 at Yerevan State University, Armenia.
This book collects some contributions presented in the annual Congress "e;Mathematical Modeling & Human Behavior"e;, held from 10 to 12 July 2024 at Universitat Politècnica de València, Valencia, Spain.
This advanced introductory textbook offers a comprehensive approach to non-relativistic Quantum Mechanics, focusing on exact methods and mathematical techniques often overlooked in standard textbooks.
This book explores the reconstruction, extension, and enhancement of the Apollo targeting and guidance algorithms, integrating original guidance concepts with new analytical solutions.
This book addresses contemporary issues in the philosophy of mathematics that deal with the role of mathematics in explanations of empirical phenomena.
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "e;Augmented Gaussian Process"e; methodology.
Among several main formulations, the book treats inverse problems with single measurements by Carleman estimates and describes a method for proving the uniqueness and the stability for the first-order transport equations, parabolic equations, and hyperbolic equations.
This book uses R package, iForecast, to conduct financial economic time series forecasting with machine learning methods, especially the generation of dynamic forecasts out-of-sample.
Graph minor theory is one of the most influential and well-developed areas of graph theory, yet its key results, particularly the work of Robertson and Seymour, have remained scattered across numerous technical papers.
This book explores the reconstruction, extension, and enhancement of the Apollo targeting and guidance algorithms, integrating original guidance concepts with new analytical solutions.
This book, the second of two volumes, focuses on scientific cognition, computationalism, and scholars' reception of what Lorenzo Magnani named "e;eco-cognitive"e; views on the mind.
This book, the second of two volumes, focuses on scientific cognition, computationalism, and scholars' reception of what Lorenzo Magnani named "e;eco-cognitive"e; views on the mind.
