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- catalog contributor b12339849.
- catalog contributor b12339850.
- catalog created "c2002.".
- catalog date "2002".
- catalog date "c2002.".
- catalog dateCopyrighted "c2002.".
- catalog description "Ch. 1. Introduction -- 1.1. What are Monte Carlo Methods? -- 1.2. Review of Basic Probability and Statistics Terminology -- Ch. 2. Generating Random Numbers -- 2.1. The General Problem -- 2.2. Pseudo-Random Number Generators -- 2.3. Generating Random Variates with Non-Uniform Distribution -- Ch. 3. Variance Reduction Techniques -- 3.1. The Basic Problem -- 3.2. Stratified Sampling -- 3.3. Importance Sampling -- 3.4. Common Random Numbers -- 3.5. Control Variates -- 3.6. Antithetic Variates -- Ch. 4. Markov Chain Monte Carlo -- 4.1. Discrete Markov Chains -- 4.2. Uniform Generation by Markov Chain Monte Carlo -- 4.3. The Metropolis Algorithm -- 4.4. Simulated Annealing -- 4.5. The Gibbs Sampler -- 4.6. The Gibbs Sampler in Bayesian Statistics -- Ch. 5. Statistical Analysis of Simulation Output -- 5.1. The Case of I.I.D. Output -- 5.2. The Case of Stationary Output -- 5.3. The Case of Asymptotically Stationary Output -- Ch. 6. The Ising Model and Related Examples -- 6.1. Definitions and Background -- 6.2. Metropolis Algorithm and Gibbs Sampler -- 6.3. Variants of the Ising Model -- 6.4. Image Analysis -- A Brief Example -- 6.5. The Swendsen-Wang Algorithm.".
- catalog description "Includes bibliographical references (p. 101-103).".
- catalog extent "viii, 103 p. :".
- catalog identifier "0821829785 (alk. paper)".
- catalog isPartOf "Fields Institute monographs, 1069-5273 ; 16".
- catalog issued "2002".
- catalog issued "c2002.".
- catalog language "eng".
- catalog publisher "Providence, R.I. : American Mathematical Society,".
- catalog subject "519.2/82 21".
- catalog subject "Monte Carlo method.".
- catalog subject "QA298 .M33 2002".
- catalog tableOfContents "Ch. 1. Introduction -- 1.1. What are Monte Carlo Methods? -- 1.2. Review of Basic Probability and Statistics Terminology -- Ch. 2. Generating Random Numbers -- 2.1. The General Problem -- 2.2. Pseudo-Random Number Generators -- 2.3. Generating Random Variates with Non-Uniform Distribution -- Ch. 3. Variance Reduction Techniques -- 3.1. The Basic Problem -- 3.2. Stratified Sampling -- 3.3. Importance Sampling -- 3.4. Common Random Numbers -- 3.5. Control Variates -- 3.6. Antithetic Variates -- Ch. 4. Markov Chain Monte Carlo -- 4.1. Discrete Markov Chains -- 4.2. Uniform Generation by Markov Chain Monte Carlo -- 4.3. The Metropolis Algorithm -- 4.4. Simulated Annealing -- 4.5. The Gibbs Sampler -- 4.6. The Gibbs Sampler in Bayesian Statistics -- Ch. 5. Statistical Analysis of Simulation Output -- 5.1. The Case of I.I.D. Output -- 5.2. The Case of Stationary Output -- 5.3. The Case of Asymptotically Stationary Output -- Ch. 6. The Ising Model and Related Examples -- 6.1. Definitions and Background -- 6.2. Metropolis Algorithm and Gibbs Sampler -- 6.3. Variants of the Ising Model -- 6.4. Image Analysis -- A Brief Example -- 6.5. The Swendsen-Wang Algorithm.".
- catalog title "Lectures on Monte Carlo methods / Neal Madras.".
- catalog type "text".