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evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to;
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applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally;
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applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally;
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Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run * Discrete-event simulation;
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for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for;
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This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and;
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-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex;
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-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex;
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This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a;
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, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios;
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focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation;
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an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and;
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Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book illustrates abstract;
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weights, here the simulation is carried out using Quasi-Monte Carlo methods in order to improve the efficiency. Despite some previous work on;
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Helping you become a creative, logical thinker and skillful simulator, Monte Carlo Simulation for the Pharmaceutical Industry: Concepts;
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Helping you become a creative, logical thinker and skillful simulator, Monte Carlo Simulation for the Pharmaceutical Industry: Concepts;
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In Monte Carlo Methods in Chemical Physics: An Introduction to the Monte Carlo Method for Particle Simulations J. Ilja Siepmann Random;
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general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available;
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This work is a useful reference book of classic research and new writing on the methodologies and applications of Monte Carlo simulation;
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Optionsbewertung Mit Monte-Carlo-Simulation is een boek van Stefano Gioia;
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simulation to solve statistical problems. Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a;
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Developed from the author's course on Monte Carlo simulation at Brown University, Monte Carlo Simulation with Applications to Finance;
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Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to;
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illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation. Each chapter contains a good selection;
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illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation. Each chapter contains a good selection;
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Graduate textbook on simulation methods in statistical physics.;
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(through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference;
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