Simulating Copulas Stochastic Models Sampling Algorithms And Applications Second Edition
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Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Second Edition) by Scherer Matthias,Mai Jan-frederik Pdf
The book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.
Simulating Copulas by Jan-Frederik Mai,Matthias Scherer Pdf
This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology. Errata(s) Errata (128 KB) Sample Chapter(s) Chapter 1: Introduction (1,016 KB) Chapter 4: Elliptical Copulas (857 KB) Contents:IntroductionArchimedean CopulasMarshall–Olkin CopulasElliptical CopulasPair Copula ConstructionsSampling Univariate Random VariablesThe Monte Carlo Method Readership: Advanced undergraduate and graduate students in probability calculus and stochastics, practitioners who implement models in the financial industry and scientists. Keywords:Copula;Simulation;Monte Carlo;Random Vector;Dependence ModelKey Features:Explicit focus on stochastic representations of copulas in contrast to an analytical perspectiveEasy-to-implement simulation schemes given as pseudo codeExplicit focus on high-dimensional modelsFocus on applicability of models, e.g. to portfolio credit risk or insuranceReviews:“The book is essentially self-contained, as the reader interested in copulas from the simulation point of view will find all necessary material in it, including an introduction to copulas if he has never been exposed to them. Both the theoretical and practical frameworks emerge quite clearly from the book. In any case, the rich bibliography contains all the references required for further in-depth analyses of specific issues. I think that the authors did a very good job, filling a gap in the statistical literature and providing a contribution that is going to be particularly helpful to statisticians without a specific background in copulas. ”Mathematical Reviews
Macroprudential Supervision in Insurance by J. Monkiewicz,M. Malecki,Marian Ma?ecki Pdf
Macroprudential policies, tools and supervision have become important since the last financial crisis. This book addresses general and methodological issues and provides a framework for the analysis of macroprudential policies and supervision in insurance. It focuses on policy related issues and global level aspects of macroprudential in insurance.
Tropical Ecosystems in the 21st Century by Anonim Pdf
Advances in Ecological Research, Volume 62, the latest release in this ongoing series, covers a long list of topics, including Monitoring tropical insects in the 21st Century, The distribution and structure of long-term and large-scale fire manipulation experiments, The Agua Salud Project: Basic and applied research informing management of tropical landscapes for the 21st century, Conservation strategies and principles for tropical forests, Assessing forest quality using satellite remote sensing data: A test case using the Sabah Biodiversity Experiment, eDNA approaches to understand the current state and future of biodiversity of the Amazonian biome: pitfalls, improvements and challenges, and much more. Provides information that relates to a thorough understanding of the field of ecology Deals with topical and important reviews on the physiologies, populations and communities of plants and animals
Vector Generalized Linear and Additive Models by Thomas W. Yee Pdf
This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs. The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.
Topics in Statistical Simulation by V.B. Melas,Stefania Mignani,Paola Monari,Luigi Salmaso Pdf
The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation. This international conference was devoted to statistical techniques in stochastic simulation, data collection, analysis of scientific experiments, and studies representing broad areas of interest. The previous workshops took place in St. Petersburg, Russia in 1994, 1996, 1998, 2001, 2005, and 2009. The Seventh Workshop took place in the Rimini Campus of the University of Bologna, which is in Rimini’s historical center.
Copulas and Dependence Models with Applications by Manuel Úbeda Flores,Enrique de Amo Artero,Fabrizio Durante,Juan Fernández Sánchez Pdf
This book presents contributions and review articles on the theory of copulas and their applications. The authoritative and refereed contributions review the latest findings in the area with emphasis on “classical” topics like distributions with fixed marginals, measures of association, construction of copulas with given additional information, etc. The book celebrates the 75th birthday of Professor Roger B. Nelsen and his outstanding contribution to the development of copula theory. Most of the book’s contributions were presented at the conference “Copulas and Their Applications” held in his honor in Almería, Spain, July 3-5, 2017. The chapter 'When Gumbel met Galambos' is published open access under a CC BY 4.0 license.
Simulation and Inference for Stochastic Differential Equations by Stefano M. Iacus Pdf
This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.
Safety and Reliability – Safe Societies in a Changing World by Stein Haugen,Anne Barros,Coen van Gulijk,Trond Kongsvik,Jan Erik Vinnem Pdf
Safety and Reliability – Safe Societies in a Changing World collects the papers presented at the 28th European Safety and Reliability Conference, ESREL 2018 in Trondheim, Norway, June 17-21, 2018. The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk management Safety and Reliability – Safe Societies in a Changing World will be invaluable to academics and professionals working in a wide range of industrial and governmental sectors: offshore oil and gas, nuclear engineering, aeronautics and aerospace, marine transport and engineering, railways, road transport, automotive engineering, civil engineering, critical infrastructures, electrical and electronic engineering, energy production and distribution, environmental engineering, information technology and telecommunications, insurance and finance, manufacturing, marine transport, mechanical engineering, security and protection, and policy making.
Simulating Copulas by Jan-Frederik Mai,Matthias Scherer Pdf
This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.
Simulation and the Monte Carlo Method by Reuven Y. Rubinstein,Dirk P. Kroese Pdf
This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as importance (re-)sampling, and the transform likelihood ratio method, the score function method for sensitivity analysis, the stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization, the cross-entropy method for rare events estimation and combinatorial optimization, and application of Monte Carlo techniques for counting problems. An extensive range of exercises is provided at the end of each chapter, as well as a generous sampling of applied examples. The Third Edition features a new chapter on the highly versatile splitting method, with applications to rare-event estimation, counting, sampling, and optimization. A second new chapter introduces the stochastic enumeration method, which is a new fast sequential Monte Carlo method for tree search. In addition, the Third Edition features new material on: • Random number generation, including multiple-recursive generators and the Mersenne Twister • Simulation of Gaussian processes, Brownian motion, and diffusion processes • Multilevel Monte Carlo method • New enhancements of the cross-entropy (CE) method, including the “improved” CE method, which uses sampling from the zero-variance distribution to find the optimal importance sampling parameters • Over 100 algorithms in modern pseudo code with flow control • Over 25 new exercises Simulation and the Monte Carlo Method, Third Edition is an excellent text for upper-undergraduate and beginning graduate courses in stochastic simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method. Reuven Y. Rubinstein, DSc, was Professor Emeritus in the Faculty of Industrial Engineering and Management at Technion-Israel Institute of Technology. He served as a consultant at numerous large-scale organizations, such as IBM, Motorola, and NEC. The author of over 100 articles and six books, Dr. Rubinstein was also the inventor of the popular score-function method in simulation analysis and generic cross-entropy methods for combinatorial optimization and counting. Dirk P. Kroese, PhD, is a Professor of Mathematics and Statistics in the School of Mathematics and Physics of The University of Queensland, Australia. He has published over 100 articles and four books in a wide range of areas in applied probability and statistics, including Monte Carlo methods, cross-entropy, randomized algorithms, tele-traffic c theory, reliability, computational statistics, applied probability, and stochastic modeling.
David R. Mandel,Gorka Navarrete,Nathan Dieckmann,Jonathan D. Nelson
Author : David R. Mandel,Gorka Navarrete,Nathan Dieckmann,Jonathan D. Nelson Publisher : Frontiers Media SA Page : 224 pages File Size : 45,8 Mb Release : 2019-09-26 Category : Electronic ISBN : 9782889630349
Judgment and Decision Making Under Uncertainty: Descriptive, Normative, and Prescriptive Perspectives by David R. Mandel,Gorka Navarrete,Nathan Dieckmann,Jonathan D. Nelson Pdf
Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods; the second half discusses model-specific al.
Recent Advances In Stochastic Modeling And Data Analysis by Christos H Skiadas Pdf
This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.
