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Money market. Capital market --- Operational research. Game theory --- Monte Carlo method. --- Business mathematics. --- Monte-Carlo, Méthode de --- Mathématiques financières --- AA / International- internationaal --- 305.975 --- Monte Carlo method --- -Business mathematics --- Business mathematics --- -519.282 --- Arithmetic, Commercial --- Business --- Business arithmetic --- Business math --- Commercial arithmetic --- Finance --- Mathematics --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Monte Carlo methods. Experimenten en resultaten. --- Electronic information resources --- Monte-Carlo, Méthode de --- Mathématiques financières --- 519.282 --- Monte Carlo methods. Experimenten en resultaten

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A Lévy process is a continuous-time analogue of a random walk, and as such, is at the cradle of modern theories of stochastic processes. Martingales, Markov processes, and diffusions are extensions and generalizations of these processes. In the past, representatives of the Lévy class were considered most useful for applications to either Brownian motion or the Poisson process. Nowadays the need for modeling jumps, bursts, extremes and other irregular behavior of phenomena in nature and society has led to a renaissance of the theory of general Lévy processes. Researchers and practitioners in fields as diverse as physics, meteorology, statistics, insurance, and finance have rediscovered the simplicity of Lévy processes and their enormous flexibility in modeling tails, dependence and path behavior. This volume, with an excellent introductory preface, describes the state-of-the-art of this rapidly evolving subject with special emphasis on the non-Brownian world. Leading experts present surveys of recent developments, or focus on some most promising applications. Despite its special character, every topic is aimed at the non- specialist, keen on learning about the new exciting face of a rather aged class of processes. An extensive bibliography at the end of each article makes this an invaluable comprehensive reference text. For the researcher and graduate student, every article contains open problems and points out directions for futurearch. The accessible nature of the work makes this an ideal introductory text for graduate seminars in applied probability, stochastic processes, physics, finance, and telecommunications, and a unique guide to the world of Lévy processes. .

Stochastic processes --- Lévy processes. --- Lévy processes --- 519.282 --- Random walks (Mathematics) --- Probabilities. --- Applied mathematics. --- Engineering mathematics. --- Operations research. --- Management science. --- Probability Theory and Stochastic Processes. --- Applications of Mathematics. --- Operations Research, Management Science. --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Engineering --- Engineering analysis --- Mathematical analysis --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk

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Simulation and Monte Carlo is aimed at students studying for degrees in Mathematics, Statistics, Financial Mathematics, Operational Research, Computer Science, and allied subjects, who wish an up-to-date account of the theory and practice of Simulation. Its distinguishing features are in-depth accounts of the theory of Simulation, including the important topic of variance reduction techniques, together with illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation. Each chapter contains a good selection of exercises and solutions with an accompanying appendix comprising a Maple worksheet containing simulation procedures. The worksheets can also be downloaded from the web site supporting the book. This encourages readers to adopt a hands-on approach in the effective design of simulation experiments. Arising from a course taught at Edinburgh University over several years, the book will also appeal to practitioners working in the finance industry, statistics and operations research.

Probability theory --- Operational research. Game theory --- Monte Carlo method. --- Simulation methods --- Business mathematics. --- Monte-Carlo, Méthode de --- Simulation, Méthodes de --- Mathématiques financières --- Monte Carlo method --- Simulation method --- Business mathematics --- Simulation method. --- 519.245 --- Stochastic approximation. Monte Carlo methods --- -Simulation method --- -Business mathematics --- -519.282 --- Arithmetic, Commercial --- Business --- Business arithmetic --- Business math --- Commercial arithmetic --- Finance --- Mathematics --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Electronic information resources --- E-books --- Méthodes de simulation --- 519.245 Stochastic approximation. Monte Carlo methods --- Monte-Carlo, Méthode de --- Méthodes de simulation --- Mathématiques financières

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Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible introductory treatment of the subject that also emphasizes recent penalized regression spline approaches to GAMs and the mixed model extensions of these models. Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and related advanced models, enabling informed use of these very flexible tools. The author bases his approach on a framework of penalized regression splines, and builds a well-grounded foundation through motivating chapters on linear and generalized linear models. While firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of the freely available R software helps explain the theory and illustrates the practicalities of linear, generalized linear, and generalized additive models, as well as their mixed effect extensions.

Mathematical logic --- Mathematical statistics --- Random walks (Mathematics) --- Linear models (Statistics) --- R (Computer program language) --- 519.22 --- 512.64 --- 57.087.1 --- -519.282 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Models, Linear (Statistics) --- Mathematical models --- Statistics --- Additive process (Probability theory) --- Random walk process (Mathematics) --- Walks, Random (Mathematics) --- Stochastic processes --- Mathematical models. --- Statistical theory. Statistical models. Mathematical statistics in general --- Linear and multilinear algebra. Matrix theory --- Biometry. Statistical study and treatment of biological data --- 57.087.1 Biometry. Statistical study and treatment of biological data --- 512.64 Linear and multilinear algebra. Matrix theory --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general --- Linear models (Statistics). --- Random walks (Mathematics). --- Promenades aléatoires (Mathématiques) --- Modèles linéaires (Statistique) --- R (Langage de programmation) --- Modèles mathématiques --- -Mathematical models