Explorations in Monte Carlo Methods |
Autore | Shonkwiler Ronald W |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
Descrizione fisica | 1 online resource (290 pages) |
Disciplina | 518.282 |
Altri autori (Persone) | MendivilFranklin |
Collana | Undergraduate Texts in Mathematics Series |
ISBN |
9783031559648
9783031559631 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface to the Second Edition -- Preface to the First Edition -- Acknowledgments -- Contents -- Notations -- 1 Introduction to Monte Carlo Methods -- 1.1 How Can Random Numbers Solve Problems? -- 1.1.1 History of the Monte Carlo Method -- 1.1.2 Histogramming Simulation Results -- 1.1.3 Sample Paths -- 1.2 Some Basic Probability -- 1.2.1 Events and Random Variables -- 1.2.2 Discrete and Continuous Random Variables -- 1.2.3 The Probability Density Function -- 1.2.4 Expected Values -- 1.2.5 Conditional Probabilities -- 1.2.6 Bayes' Formula -- 1.2.7 Joint Probability Distributions -- 1.3 Random Number Generation -- 1.3.1 Requirements for a Random Number Generator (RNG) -- 1.3.2 Middle-Square and Other Middle-Digit Techniques -- 1.3.3 Linear Congruential Random Number Generators -- 1.4 Some Applications -- 2 Some Probability Distributions and Their Uses -- 2.1 CDF Inversion-Discrete Case Example: Bernoulli Trials -- 2.1.1 Two-Outcome CDF Inversion -- 2.1.2 Multiple-Outcome Distributions -- 2.2 Walker's Alias Method Example: Roulette Wheel Selection -- 2.3 Probability Simulation Example: The Binomial Distribution -- 2.3.1 Sampling from the Binomial -- 2.4 Another Simulation Example: The Poisson Distribution -- 2.4.1 Sampling from the Poisson Distribution by Simulation -- 2.5 CDF Inversion, Continuous Case Example: The Exponential Distribution -- 2.5.1 Inverting the CDF-The Canonical Method for the Exponential -- 2.5.2 Discrete Event Simulation -- 2.5.3 Transforming Random Variables, the Cauchy Distribution -- 2.6 The Central Limit Theorem and the Normal Distribution -- 2.6.1 Sampling from the Normal Distribution -- 2.6.2 Approximate Sampling via the Central Limit Theorem -- 2.6.3 Error Estimates for Monte Carlo Simulations -- 2.7 Gibrat's Law and the Lognormal Distribution -- 2.8 Rejection Sampling Example: The Beta Distribution.
2.8.1 The Beta Distribution -- 2.8.2 Sampling from an Unbounded Beta Distribution -- 2.9 Composite Distributions: Sampling the Gamma Distribution -- 2.9.1 The Gamma Distribution -- 2.9.2 Sampling from upper G left parenthesis alpha comma 1 right parenthesisG(α,1) -- 2.10 Sampling from a Joint Distribution -- 3 Markov Chain Monte Carlo -- 3.1 Discrete Markov Chains -- 3.1.1 Random Walk on a Graph -- 3.1.2 Matrix Representation of a Chain -- 3.2 Markov Chain Monte Carlo Sampling- The Metropolis Algorithm -- 3.2.1 Some Examples -- 3.2.2 Why Does the Metropolis Algorithm Work? -- 3.3 MCMC Sampling and the Ergodic Theorem -- 3.4 Statistical Mechanics -- 3.5 Ising Model and the Metropolis Algorithm -- 3.6 The Metropolis-Hastings Algorithm -- 3.7 Counting -- 3.8 Some Applications of MCMC -- 3.8.1 Shuffling with Constraints -- 3.8.2 Coupling from the Past -- 4 Random Walks -- 4.1 1d Random Walk -- 4.2 Diffusion -- 4.3 Brownian Motion -- 4.4 Random Walk Applications I -- 4.4.1 Options Pricing in Finance -- 4.4.2 Self-Avoiding Walks -- 4.5 Gambler's Ruin -- 4.5.1 Gambling Schemes -- 4.6 Random Walk Applications II-Kelly's Criterion in Finance -- 4.6.1 The Simple Kelly Game -- 4.6.2 The Simple Game with Catastrophic Loss -- 4.6.3 Option Trading Application I -- 4.6.4 Option Trading Application II -- 4.7 Random Walks and Electrical Networks -- 4.7.1 Markov Chain Solution for Voltages -- 4.7.2 The Fundamental Matrix and Expected Hitting Times -- 4.8 The Kinetic Monte Carlo Method -- 5 Optimization by Monte Carlo Methods -- 5.1 Simulated Annealing -- 5.2 Application of SA to the Traveling Salesman Problem -- 5.3 Genetic Algorithms -- 5.4 An Application of GA to Function Maximization -- 5.5 An Application of GA to the Permanent Problem -- 6 More on Markov Chain Monte Carlo -- 6.1 Bayesian Inference -- 6.1.1 Pymc3 -- 6.2 Gibbs Sampling. 6.3 Monte Carlo Integration: Quadrature -- 6.3.1 Variance Reduction -- 6.3.2 MCMC in Quadrature -- 6.4 Round-off Error -- Appendix A Generating Uniform Random Numbers -- A.1 Multiple Stored Value Random Number Generation -- A.1.1 Fibonacci Generators -- A.1.2 Finite Field RNG -- A.2 Mersenne Twister -- A.3 Testing for Non-randomness -- A.3.1 Chi-Square Test -- A.3.2 Kolmogorov-Smirnov Test -- Appendix B Perron-Frobenius Theorem -- B.1 Proof of Perron-Frobenius -- Appendix C Kelly Allocation for Correlated Investments -- C.1 Kelly Allocation for Correlated Investments -- C.2 Genetic Algorithm Code for the Kelly Problem -- Appendix D Donsker's Theorem -- D.1 Donsker's Theorem -- Appendix E Projects -- Appendix References -- -- Index -- Code Index. |
Record Nr. | UNINA-9910865269003321 |
Shonkwiler Ronald W
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Cham : , : Springer, , 2024 | ||
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Lo trovi qui: Univ. Federico II | ||
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Handbook for Monte Carlo methods [Risorsa elettronica] / Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev |
Autore | Kroese, Dirk P. |
Pubbl/distr/stampa | Hoboken, N.J. : Wiley, 2011 |
Disciplina | 518.282 |
Altri autori (Persone) |
Taimre, Thomas <1983- >
Botev, Zdravko I. <1982- > |
Collana | Wiley series in probability and statistics |
ISBN | 9781118014967 |
Formato | Risorse elettroniche ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-990009821810403321 |
Kroese, Dirk P.
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Hoboken, N.J. : Wiley, 2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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Introducing Monte Carlo methods with R / Christian P. Robert, George Casella |
Autore | Robert, Christian P. |
Pubbl/distr/stampa | New York : Springer, 2010 |
Descrizione fisica | XV, 283 p. : ill. ; 24 cm |
Disciplina | 518.282 |
Altri autori (Persone) | Casella, George |
Collana | Use R! |
Soggetto non controllato | Metodo Monte Carlo |
ISBN | 978-1-4419-1575-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-990009909830403321 |
Robert, Christian P.
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New York : Springer, 2010 | ||
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Lo trovi qui: Univ. Federico II | ||
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An introduction to kinetic Monte Carlo simulations of surface reactions / / A.P.J. Jansen |
Autore | Jansen A. P. J |
Edizione | [1st ed. 2012.] |
Pubbl/distr/stampa | Berlin ; ; Heidelberg, : Springer, c2012 |
Descrizione fisica | 1 online resource (XVII, 254 p. 79 illus.) |
Disciplina | 518.282 |
Collana | Lecture notes in physics |
Soggetto topico |
Monte Carlo method
Numerical analysis |
ISBN | 3-642-29488-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction -- Stochastic Model for the Description of Surface Reaction Systems -- Kinetic Monte Carlo Algorithms -- How to Get Kinetic Parameters -- Modeling Surface Reactions I -- Modeling Surface Reactions II -- Examples -- New Developments -- Glossary -- Index. |
Record Nr. | UNINA-9910133760803321 |
Jansen A. P. J
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Berlin ; ; Heidelberg, : Springer, c2012 | ||
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Lo trovi qui: Univ. Federico II | ||
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Markov Chain Monte Carlo Methods in Quantum Field Theories : A Modern Primer / / by Anosh Joseph |
Autore | Joseph Anosh |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (XIV, 126 p. 36 illus.) |
Disciplina |
530.143
518.282 |
Collana | SpringerBriefs in Physics |
Soggetto topico |
Physics
Elementary particles (Physics) Quantum field theory String theory Numerical and Computational Physics, Simulation Elementary Particles, Quantum Field Theory Quantum Field Theories, String Theory |
ISBN | 3-030-46044-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Monte Carlo Method for Integration -- Monte Carlo with Importance Sampling -- Markov Chains -- Markov Chain Monte Carlo -- MCMC and Feynman Path Integrals -- Reliability of Simulations -- Hybrid (Hamiltonian) Monte Carlo -- MCMC and Quantum Field Theories on a Lattice -- Machine Learning and Quantum Field Theories -- C++ Programs. |
Record Nr. | UNINA-9910741164703321 |
Joseph Anosh
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Monte Carlo : concepts, algorithms, and applications / George S. Fishman |
Autore | Fishman, George Samuel |
Edizione | [Corrected 3. printing] |
Pubbl/distr/stampa | New York, : Springer, stampa 1999 |
Descrizione fisica | XXV, 690 ; 25 cm. |
Disciplina |
518
518.282 |
Collana | Springer series in operations research |
ISBN | 038794527X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISANNIO-NAP0423667 |
Fishman, George Samuel
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New York, : Springer, stampa 1999 | ||
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Lo trovi qui: Univ. del Sannio | ||
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Monte Carlo and Quasi-Monte Carlo methods : MCQMC 2020, Oxford, United Kingdom, August 10-14 / / edited by Alexander Keller |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (315 pages) |
Disciplina | 518.282 |
Collana | Springer Proceedings in Mathematics and Statistics |
Soggetto topico |
Monte Carlo method
Mètode de Montecarlo |
Soggetto genere / forma |
Congressos
Llibres electrònics |
ISBN |
9783030983192
9783030983185 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910574057803321 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. Federico II | ||
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Monte Carlo and Quasi-Monte Carlo methods : MCQMC 2020, Oxford, United Kingdom, August 10-14 / / edited by Alexander Keller |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (315 pages) |
Disciplina | 518.282 |
Collana | Springer Proceedings in Mathematics and Statistics |
Soggetto topico |
Monte Carlo method
Mètode de Montecarlo |
Soggetto genere / forma |
Congressos
Llibres electrònics |
ISBN |
9783030983192
9783030983185 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996479369203316 |
Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Monte Carlo and quasi-Monte Carlo methods 2012 / / Josef Dick, Frances Y. Kuo, Gareth W. Peters, Ian H. Sloan, editors |
Edizione | [1st ed. 2013.] |
Pubbl/distr/stampa | Heidelberg, Germany : , : Springer, , 2013 |
Descrizione fisica | 1 online resource (xii, 686 pages) : illustrations (some color) |
Disciplina | 518.282 |
Collana | Springer Proceedings in Mathematics & Statistics |
Soggetto topico | Monte Carlo method |
ISBN | 3-642-41095-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Part I: Invited Articles -- Part II: Tutorial -- Part III: Contributed Articles -- Conference Participants -- Index. |
Record Nr. | UNINA-9910438157303321 |
Heidelberg, Germany : , : Springer, , 2013 | ||
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Lo trovi qui: Univ. Federico II | ||
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Monte Carlo methods [[electronic resource] /] / Malvin H. Kalos, Paula A. Whitlock |
Autore | Kalos Malvin H |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Weinheim, : Wiley-Blackwell, c2008 |
Descrizione fisica | 1 online resource (217 p.) |
Disciplina | 518.282 |
Altri autori (Persone) | WhitlockPaula A |
Soggetto topico | Monte Carlo method |
Soggetto genere / forma | Electronic books. |
ISBN |
1-62198-230-0
1-282-68811-1 9786612688119 3-527-62621-2 3-527-62622-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Monte Carlo Methods; Contents; Preface to the Second Edition; Preface to the First Edition; 1 What is Monte Carlo?; 1.1 Introduction; 1.2 Topics to be Covered; 1.3 A Short History of Monte Carlo; References; 2 A Bit of Probability; 2.1 Random Events; 2.2 Random Variables; 2.2.1 The Binomial Distribution; 2.2.2 The Geometric Distribution; 2.2.3 The Poisson Distribution; 2.3 Continuous Random Variables; 2.4 Expectations of Continuous Random Variables; 2.5 Bivariate Continuous Random Distributions; 2.6 Sums of Random Variables: Monte Carlo Quadrature
2.7 Distribution of the Mean of a Random Variable: A Fundamental Theorem2.8 Distribution of Sums of Independent Random Variables; 2.9 Monte Carlo Integration; 2.10 Monte Carlo Estimators; References; Further Reading; Elementary; More Advanced; 3 Sampling Random Variables; 3.1 Transformation of Random Variables; 3.2 Numerical Transformation; 3.3 Sampling Discrete Distributions; 3.4 Composition of Random Variables; 3.4.1 Sampling the Sum of Two Uniform Random Variables; 3.4.2 Sampling a Random Variable Raised to a Power; 3.4.3 Sampling the Distribution f(z) = z(1 - z) 3.4.4 Sampling the Sum of Several Arbitrary Distributions3.5 Rejection Techniques; 3.5.1 Sampling a Singular pdf Using Rejection; 3.5.2 Sampling the Sine and Cosine of an Angle; 3.5.3 Kahn's Rejection Technique for a Gaussian; 3.5.4 Marsaglia et al. Method for Sampling a Gaussian; 3.6 Multivariate Distributions; 3.6.1 Sampling a Brownian Bridge; 3.7 The M(RT)2 Algorithm; 3.8 Application of M(RT)2; 3.9 Testing Sampling Methods; References; Further Reading; 4 Monte Carlo Evaluation of Finite-Dimensional Integrals; 4.1 Importance Sampling; 4.2 The Use of Expected Values to Reduce Variance 4.3 Correlation Methods for Variance Reduction4.3.1 Antithetic Variates; 4.3.2 Stratification Methods; 4.4 Adaptive Monte Carlo Methods; 4.5 Quasi-Monte Carlo; 4.5.1 Low-Discrepancy Sequences; 4.5.2 Error Estimation for Quasi-Monte Carlo Quadrature; 4.5.3 Applications of Quasi-Monte Carlo; 4.6 Comparison of Monte Carlo Integration, Quasi-Monte Carlo and Numerical Quadrature; References; Further Reading; 5 Random Walks, Integral Equations, and Variance Reduction; 5.1 Properties of Discrete Markov Chains; 5.1.1 Estimators and Markov Processes; 5.2 Applications Using Markov Chains 5.2.1 Simulated Annealing5.2.2 Genetic Algorithms; 5.2.3 Poisson Processes and Continuous Time Markov Chains; 5.2.4 Brownian Motion; 5.3 Integral Equations; 5.3.1 Radiation Transport and Random Walks; 5.3.2 The Boltzmann Equation; 5.4 Variance Reduction; 5.4.1 Importance Sampling of Integral Equations; References; Further Reading; 6 Simulations of Stochastic Systems: Radiation Transport; 6.1 Radiation Transport as a Stochastic Process; 6.2 Characterization of the Source; 6.3 Tracing a Path; 6.4 Modeling Collision Events; 6.5 The Boltzmann Equation and Zero Variance Calculations 6.5.1 Radiation Impinging on a Slab |
Record Nr. | UNINA-9910143138003321 |
Kalos Malvin H
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Weinheim, : Wiley-Blackwell, c2008 | ||
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Lo trovi qui: Univ. Federico II | ||
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