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Montana: a Cultural Medley
by Robert R. Jr. SwartoutThe whole is greater than the sum of the parts when Montana historian Robert Swartout gathers the fascinating stories of the state's surprisingly diverse ethnic groups into this thought-provoking collection of essays. Fourteen chapters showcase an African American nightclub in Great Falls, a Japanese American war hero, the founding of a Metís community, Jewish merchants, and Dutch settlement in the Gallatin Valley, as well as stories of Irish, Scots, Chinese, Finns, Mexican Americans, European war brides, and more.
Monte Carlo Methods
by Adrian Barbu Song-Chun ZhuThis book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.
Monte Carlo Methods Utilizing Mathematica®: Applications in Inverse Transform and Acceptance-Rejection Sampling (Synthesis Lectures on Mathematics & Statistics)
by Sujaul ChowdhuryThis book provides practical demonstrations of how to carry out definite integrals with Monte Carlo methods using Mathematica. Random variates are sampled by the inverse transform method and the acceptance-rejection method using uniform, linear, Gaussian, and exponential probability distribution functions. A chapter on the application of the Variational Quantum Monte Carlo method to a simple harmonic oscillator is included. These topics are all essential for students of mathematics and physics. The author includes thorough background on each topic covered within the book in order to help readers understand the subject. The book also contains many examples to show how the methods can be applied.
Monte Carlo Methods and Models in Finance and Insurance (Chapman and Hall/CRC Financial Mathematics Series)
by Ralf Korn Elke Korn Gerald KroisandtOffering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom
Monte Carlo Methods for Electromagnetics
by Matthew N.O. SadikuUntil now, novices had to painstakingly dig through the literature to discover how to use Monte Carlo techniques for solving electromagnetic problems. Written by one of the foremost researchers in the field, Monte Carlo Methods for Electromagnetics provides a solid understanding of these methods and their applications in electromagnetic computation. Including much of his own work, the author brings together essential information from several different publications.Using a simple, clear writing style, the author begins with a historical background and review of electromagnetic theory. After addressing probability and statistics, he introduces the finite difference method as well as the fixed and floating random walk Monte Carlo methods. The text then applies the Exodus method to Laplace’s and Poisson’s equations and presents Monte Carlo techniques for handing Neumann problems. It also deals with whole field computation using the Markov chain, applies Monte Carlo methods to time-varying diffusion problems, and explores wave scattering due to random rough surfaces. The final chapter covers multidimensional integration.Although numerical techniques have become the standard tools for solving practical, complex electromagnetic problems, there is no book currently available that focuses exclusively on Monte Carlo techniques for electromagnetics. Alleviating this problem, this book describes Monte Carlo methods as they are used in the field of electromagnetics.
Monte Carlo Methods for Particle Transport
by Alireza HaghighatFully updated with the latest developments in the eigenvalue Monte Carlo calculations and automatic variance reduction techniques and containing an entirely new chapter on fission matrix and alternative hybrid techniques. This second edition explores the uses of the Monte Carlo method for real-world applications, explaining its concepts and limitations. Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, it is an ideal textbook and practical guide for nuclear engineers and scientists looking into the applications of the Monte Carlo method, in addition to students in physics and engineering, and those engaged in the advancement of the Monte Carlo methods. Describes general and particle-transport-specific automated variance reduction techniques Presents Monte Carlo particle transport eigenvalue issues and methodologies to address these issues Presents detailed derivation of existing and advanced formulations and algorithms with real-world examples from the author’s research activities
Monte Carlo Methods for Radiation Transport
by Oleg N. VassilievThis book is a guide to the use of Monte Carlo techniques in radiation transport. This topic is of great interest for medical physicists. Praised as a "gold standard" for accurate radiotherapy dose calculations, Monte Carlo has stimulated a high level of research activity that has produced thousands of papers within the past few years. The book is designed primarily to address the needs of an academically inclined medical physicist who wishes to learn the technique, as well as experienced users of standard Monte Carlo codes who wish to gain insight into the underlying mathematics of Monte Carlo algorithms. The book focuses on the fundamentals--giving full attention to and explaining the very basic concepts. It also includes advanced topics and covers recent advances such as transport of charged particles in magnetic fields and the grid-based solvers of the Boltzmann equation.
Monte Carlo N-Particle Simulations for Nuclear Detection and Safeguards: An Examples-Based Guide for Students and Practitioners
by John S. Hendricks Martyn T. Swinhoe Andrea FavalliThis open access book is a pedagogical, examples-based guide to using the Monte Carlo N-Particle (MCNP®) code for nuclear safeguards and non-proliferation applications. The MCNP code, general-purpose software for particle transport simulations, is widely used in the field of nuclear safeguards and non-proliferation for numerous applications including detector design and calibration, and the study of scenarios such as measurement of fresh and spent fuel. This book fills a gap in the existing MCNP software literature by teaching MCNP software usage through detailed examples that were selected based on both student feedback and the real-world experience of the nuclear safeguards group at Los Alamos National Laboratory. MCNP input and output files are explained, and the technical details used in MCNP input file preparation are linked to the MCNP code manual. Benefiting from the authors’ decades of experience in MCNP simulation, this book is essential reading for students, academic researchers, and practitioners whose work in nuclear physics or nuclear engineering is related to non-proliferation or nuclear safeguards. Each chapter comes with downloadable input files for the user to easily reproduce the examples in the text.
Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies (Chapman & Hall/CRC Biostatistics Series)
by Mark ChangHelping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and metho
Monte Carlo Simulation in Statistical Physics: An Introduction (Graduate Texts in Physics #Vol. 80)
by Kurt Binder Dieter W. HeermannThe sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo simulation in statistical physics, which deals with the computer simulation of many-body systems in condensed matter physics and related fields of physics and beyond (traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, these powerful simulation methods calculate probability distributions, making it possible to estimate the thermodynamic properties of various systems. The book describes the theoretical background of these methods, enabling newcomers to perform such simulations and to analyse their results. It features a modular structure, with two chapters providing a basic pedagogic introduction plus exercises suitable for university courses; the remaining chapters cover major recent developments in the field.This edition has been updated with two new chapters dealing with recently developed powerful special algorithms and with finite size scaling tools for the study of interfacial phenomena, which are important for nanoscience. Previous editions have been highly praised and widely used by both students and advanced researchers.
Monte Carlo Simulation with Applications to Finance
by Hui WangDeveloped from the author's course on Monte Carlo simulation at Brown University, this text provides a self-contained introduction to Monte Carlo methods in financial engineering. It covers common variance reduction techniques, the cross-entropy method, and the simulation of diffusion process models. Requiring minimal background in mathematics and finance, the book includes numerous examples of option pricing, risk analysis, and sensitivity analysis as well as many hand-and-paper and MATLAB coding exercises at the end of every chapter.
Monte Carlo Simulations Using Microsoft EXCEL® (Synthesis Lectures on Mathematics & Statistics)
by Shinil ChoThis book offers step-by-step descriptions of various random systems and explores the world of computer simulations. In addition, this book offers a working introduction to those who want to learn how to create and run Monte Carlo simulations. Monte Carlo simulation has been a powerful computational tool for physics models, and when combined with the programming language Excel, this book is a valuable resource for readers who wish to acquire knowledge that can be applied to more complex systems. Visualization of the simulation results via the Visual Basic built in Microsoft EXCEL is presented as the first step towards the subject. Prior experience with the Excel add-in VBA is kept to a minimum. In addition, a chapter on quantum optimization simulation utilizing Python is added to explore the quantum computation. Readers will gain a fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects and other research projects.
Monte Carlo and Quasi-Monte Carlo Methods
by Ronald Cools Dirk NuyensThis book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2018, Rennes, France, July 1–6 (Springer Proceedings in Mathematics & Statistics #324)
by Bruno Tuffin Pierre L’EcuyerThis book presents the refereed proceedings of the 13th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Rennes, France, and organized by Inria, in July 2018. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2022, Linz, Austria, July 17–22 (Springer Proceedings in Mathematics & Statistics #460)
by Friedrich Pillichshammer Peter Kritzer Aicke HinrichsThis book presents the refereed proceedings of the 15th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held in Linz, Austria, and organized by the Johannes Kepler University Linz and the Austrian Academy of Sciences, in July 2022. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these highly active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, in particular arising in finance, statistics and computer graphics.
Monte Carlo and Quasi-Monte Carlo Methods: Mcqmc 2016, Stanford, Ca, August 14-19 (Springer Proceedings in Mathematics & Statistics #241)
by Peter W. Glynn Art B. OwenThis book presents the refereed proceedings of the Twelfth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at Stanford University (California) in August 2016. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising in particular, in finance, statistics, computer graphics and the solution of PDEs.
Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear
by Emmanuel GobetDeveloped from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also thoroughly develops the problem of numerical integration and computation of expectation by the Monte-Carlo method. The book begins with a history of Monte-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex distributions, and stochastic optimization. The remainder of the text is organized in three parts of progressive difficulty. The first part presents basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation of stochastic differential equations. The final part discusses the simulation of non-linear dynamics.
Monte-Carlo Simulation-Based Statistical Modeling
by Ding-Geng Din Chen John Dean ChenThis book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Monte-Carlo Simulation: An Introduction for Engineers and Scientists
by Alan StevensMonte-Carlo techniques have increasingly become a key method used in quantitative research. This book introduces engineers and scientists to the basics of using the Monte-Carlo simulation method which is used in Operations Research and other fields to understand the impact of risk and uncertainty in prediction and forecasting models. Monte-Carlo Simulation: An Introduction for Engineers and Scientists explores several specific applications in addition to illustrating the principles behind the methods. The question of accuracy and efficiency with using the method is addressed thoroughly within each chapter and all program listings are included in the discussion of each application to facilitate further research for the reader using Python programming language. Beginning engineers and scientists either already in or about to go into industry or commercial and government scientific laboratories will find this book essential. It could also be of interest to undergraduates in engineering science and mathematics, as well as instructors and lecturers who have no prior knowledge of Monte-Carlo simulations.
Montenegro: Technical Assistance Report-report On External Sector Statistics Mission (Imf Staff Country Reports)
by International Monetary Fund. Statistics Dept.A report from the International Monetary Fund.
Monthly Problem Gems
by Hongwei ChenThis book is an outgrowth of a collection of sixty-two problems offered in the The American Mathematical Monthly (AMM) the author has worked over the last two decades. Each selected problem has a central theme, contains gems of sophisticated ideas connected to important current research, and opens new vistas in the understanding of mathematics. The AMM problem section provides one of the most challenging and interesting problem sections among the various journals and online sources currently available. The published problems and solutions have become a treasure trove rife with mathematical gems. The author presents either his published solution in the AMM or an alternative solution to the published one to present and develop problem-solving techniques. A rich glossary of important theorems and formulas is included for easy reference. The reader may regard this book as a starter set for AMM problems, providing a jumping of point to new ideas, and extending their personal lexicon of problems and solutions. This collection is intended to encourage the reader to move away from routine exercises toward creative solutions, as well as offering the reader a systematic illustration of how to organize the transition from problem solving to exploring, investigating and discovering new results.
Moral Hazard in Health Insurance (Kenneth J. Arrow Lecture Series)
by Amy FinkelsteinMoral hazard—the tendency to change behavior when the cost of that behavior will be borne by others—is a particularly tricky question when considering health care. Kenneth J. Arrow's seminal 1963 paper on this topic (included in this volume) was one of the first to explore the implication of moral hazard for health care, and Amy Finkelstein—recognized as one of the world's foremost experts on the topic—here examines this issue in the context of contemporary American health care policy. Drawing on research from both the original RAND Health Insurance Experiment and her own research, including a 2008 Health Insurance Experiment in Oregon, Finkelstein presents compelling evidence that health insurance does indeed affect medical spending and encourages policy solutions that acknowledge and account for this. The volume also features commentaries and insights from other renowned economists, including an introduction by Joseph P. Newhouse that provides context for the discussion, a commentary from Jonathan Gruber that considers provider-side moral hazard, and reflections from Joseph E. Stiglitz and Kenneth J. Arrow.
Moral Hazard in Health Insurance (Kenneth J. Arrow Lecture Series)
by Amy FinkelsteinAddressing the challenge of covering heath care expenses—while minimizing economic risks. Moral hazard—the tendency to change behavior when the cost of that behavior will be borne by others—is a particularly tricky question when considering health care. Kenneth J. Arrow&’s seminal 1963 paper on this topic (included in this volume) was one of the first to explore the implication of moral hazard for health care, and Amy Finkelstein—recognized as one of the world&’s foremost experts on the topic—here examines this issue in the context of contemporary American health care policy. Drawing on research from both the original RAND Health Insurance Experiment and her own research, including a 2008 Health Insurance Experiment in Oregon, Finkelstein presents compelling evidence that health insurance does indeed affect medical spending and encourages policy solutions that acknowledge and account for this. The volume also features commentaries and insights from other renowned economists, including an introduction by Joseph P. Newhouse that provides context for the discussion, a commentary from Jonathan Gruber that considers provider-side moral hazard, and reflections from Joseph E. Stiglitz and Kenneth J. Arrow. &“Reads like a fireside chat among a group of distinguished, articulate health economists.&” —Choice
Moral Strata
by John R. WelchThis volume recreates the received notion of reflective equilibrium. It reconfigures reflective equilibrium as both a cognitive ideal and a method for approximating this ideal. The ideal of reflective equilibrium is restructured using the concept of discursive strata, which are formed by sentences and differentiated by function. Sentences that perform the same kind of linguistic function constitute a stratum. The book shows how moral discourse can be analyzed into phenomenal, instrumental, and teleological strata, and the ideal of reflective equilibrium reworked in these terms. In addition, the work strengthens the method of reflective equilibrium by harnessing the resources of decision theory and inductive logic. It launches a comparative version of decision theory and employs this framework as a guide to moral theory choice. It also recruits quantitative inductive logic to inform a standard of inductive cogency. When used in tandem with comparative decision theory, this standard can aid in the effort to turn the undesirable condition of reflective disequilibrium into reflective equilibrium.
Mordell–Weil Lattices (Ergebnisse der Mathematik und ihrer Grenzgebiete. 3. Folge / A Series of Modern Surveys in Mathematics #70)
by Matthias Schütt Tetsuji ShiodaThis book lays out the theory of Mordell–Weil lattices, a very powerful and influential tool at the crossroads of algebraic geometry and number theory, which offers many fruitful connections to other areas of mathematics. The book presents all the ingredients entering into the theory of Mordell–Weil lattices in detail, notably, relevant portions of lattice theory, elliptic curves, and algebraic surfaces. After defining Mordell–Weil lattices, the authors provide several applications in depth. They start with the classification of rational elliptic surfaces. Then a useful connection with Galois representations is discussed. By developing the notion of excellent families, the authors are able to design many Galois representations with given Galois groups such as the Weyl groups of E6, E7 and E8. They also explain a connection to the classical topic of the 27 lines on a cubic surface.Two chapters deal with elliptic K3 surfaces, a pulsating area of recent research activity which highlights many central properties of Mordell–Weil lattices. Finally, the book turns to the rank problem—one of the key motivations for the introduction of Mordell–Weil lattices. The authors present the state of the art of the rank problem for elliptic curves both over Q and over C(t) and work out applications to the sphere packing problem. Throughout, the book includes many instructive examples illustrating the theory.