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1.

図書
図書
1. Simulation and the Monte Carlo method
Reuven Y. Rubinstein
出版情報: New York : Wiley, c1981  xv, 278 p. ; 24 cm
シリーズ名: Wiley series in probability and mathematical statistics ; . Probability and mathematical statistics
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目次情報: 続きを見る
Systems, Models, Simulation and the Monte Carlo Method
Random Number Generation
Random Variate Generation
Monte Carlo Integration and Variance Reduction Techniques
Linear Equations and Markov Chains
Regenerative Method for Simulation Analysis
Monte Carlo Optimization
Appendix
Exercises
References
Index
Systems, Models, Simulation and the Monte Carlo Method
Random Number Generation
Random Variate Generation
2.

図書
図書
2. Monte Carlo principles and neutron transport problems
[by] Jerome Spanier and Ely M. Gelbard
出版情報: Reading, Mass. : Addison-Wesley Pub. Co, 1969  xiv, 234 p ; 24 cm
シリーズ名: Addison-Wesley series in computer science and information processing
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3.

図書
図書
3. The Monte Carlo method : the method of statistical trials. 1st English ed
N.P. Buslenko ... [et al.] ; edited by Yu.A. Shreider ; translated from the Russian by G.J. Tee ; translation edited by D.M. Parkyn
出版情報: Oxford : Pergamon, 1966  xii, 381 p. ; 23 cm
シリーズ名: International series of monographs on pure and applied mathematics ; v. 87
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4.

図書
図書
4. Image analysis, random fields and dynamic Monte Carlo methods : a mathematical introduction (: gw ; : us)
Gerhard Winkler
出版情報: Berlin ; New York : Springer-Verlag, c1995  xiv, 324 p. ; 24 cm
シリーズ名: Applications of mathematics ; 27
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5.

図書
図書
5. Image analysis, random fields and Markov chain Monte Carlo methods : a mathematical introduction. 2nd ed
Gerhard Winkler
出版情報: Berlin ; Tokyo : Springer, c2003  xvi, 387 p. ; 25 cm.
シリーズ名: Applications of mathematics ; 27
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目次情報: 続きを見る
Introduction
Bayesian Image Analysis: Introduction / Part I：
The Bayesian Paradigm / 1：
Warming up for Absolute Beginners / 1.1：
linages and Observations / 1.2：
Prior and Posterior Distributions / 1.3：
Bayes Estimators / 1.4：
Cleaning Dirty Pictures / 2：
Boundaries and Their Information Content / 2.1：
Towards Piccewiso Smoothing / 2.2：
Filters, Smoothers, and Bayes Estimators / 2.3：
Boundary Extraction / 2.4：
Dependence on Hyperparameters / 2.5：
Finite Random Fields / 3：
Markov Random Fields / 3.1：
Gibbs Fields and Potentials / 3.2：
Potentials Continued / 3.3：
The Gibbs Sampler and Simulated Annealing / Part II：
Markov Chains: Limit Theorems / 4：
Preliminaries / 4.1：
The Contraction Coefficient / 4.2：
Homogeneous Markov Chains / 4.3：
Exact Sampling / 4.4：
Inhomogeneous Markov Chains / 4.5：
A Law of Large Numbers for Inhomogeneous Chains / 4.6：
A Counterexample for the Law of Large Numbers / 4.7：
Gibbsian Sampling and Annealing / 5：
Sampling / 5.1：
Simulated Annealing / 5.2：
Discussion / 5.3：
Cooling Schedules / 6：
The ICM Algorithm / 6.1：
Exact MAP Estimation Versus Fast Cooling / 6.2：
Finite Time Annealing / 6.3：
Variations of the Gibbs Sampler / Part III：
Gibbsian Sampling and Annealing Revisited / 7：
A General Gibbs Sampler / 7.1：
Sampling and Annealing Under Constraints / 7.2：
Partially Parallel Algorithms / 8：
Synchronous Updating on Independent Sets / 8.1：
The Swendson-Wang Algorithm / 8.2：
Synchronous Algorithms / 9：
Invariant Distributions and Convergence / 9.1：
Support of the Limit Distribution / 9.2：
Synchronous Algorithms and Reversibility / 9.3：
Metropolis Algorithms and Spectral Methods / Part IV：
Metropolis Algorithms / 10：
Metropolis Sampling and Annealing / 10.1：
Convergence Theorems / 10.2：
Best Constants / 10.3：
About Visiting Schemes / 10.4：
Generalizations and Modifications / 10.5：
The Metropolis Algorithm in Combinatorial Optimization / 10.6：
The Spectral Gap and Convergence of Markov Chains / 11：
Eigenvalues of Markov Kernels / 11.1：
Geometric Convergence Rates / 11.2：
Eigenvalues, Sampling, Variance Reduction / 12：
Samplers and Their Eigenvalues / 12.1：
Variance Reduction / 12.2：
Importance Sampling / 12.3：
Continuous Time Processes / 13：
Discrete State Space / 13.1：
Continuous State Space / 13.2：
Texture Analysis / Part V：
Partitioning / 14：
How to Tell Textures Apart / 14.1：
Bayesian Texture Segmentation / 14.2：
Segmentation by a Boundary Model / 14.3：
Julesz's Conjecture and Two Point Processes / 14.4：
Random Fields and Texture Models / 15：
Neighbourhood Relations / 15.1：
Random Field Texture Models / 15.2：
Texture Synthesis / 15.3：
Bayesian Texture Classification / 16：
Contextual Classification / 16.1：
Marginal Posterior Modes Methods / 16.2：
Parameter Estimation / Part VI：
Maximum Likelihood Estimation / 17：
The Likelihood Function / 17.1：
Objective Functions / 17.2：
Consistency of Spatial ML Estimators / 18：
Observation Windows and Specifications / 18.1：
Pseudolikelihood Methods / 18.2：
Large Deviations and Full Maximum Likelihood / 18.3：
Partially Observed Data / 18.4：
Computation of Pull ML Estimators / 19：
A Naive Algorithm / 19.1：
Stochastic Optimization for the Full Likelihood / 19.2：
Main Results / 19.3：
Error Decomposition / 19.4：
Supplement / 19.5：
A Glance at Neural Networks / 20：
Boltzmann Machines / 20.1：
A Learning Rule / 20.2：
Three Applications / 21：
Motion Analysis / 21.1：
Tomographic Image Reconstruction / 21.2：
Biological Shape / 21.3：
Appendix / Part VIII：
Simulation of Random Variables / A：
Pseudorandom Numbers / A.1：
Discrete Random Variables / A.2：
Special Distributions / A.3：
Analytical Tools / B：
Concave Functions / B.1：
Convergence of Descent Algorithms / B.2：
A Discrete Gronwall Lemma / B.3：
A Gradient System / B.4：
Physical Imaging Systems / C：
The Software Package AntsInFields / D：
References
Symbols
Index
Introduction
Bayesian Image Analysis: Introduction / Part I：
The Bayesian Paradigm / 1：
6.

図書
図書
6. Sequential Monte Carlo methods in practice
Arnaud Doucet, Nando de Freitas, Neil Gordon, editors ; foreword by Adrian Smith
出版情報: New York : Springer, c2001  xxvii, 581 p. ; 24 cm
シリーズ名: Statistics for engineering and information science
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7.

図書
図書
7. Interdependent systems : structure and estimation (: American Elsevier ; : ne)
by Ernest J. Mosbaek and Herman O. Wold ; with contributions by Ejnar Lyttkens, Anders Ågren and Lennart Bodin
出版情報: Amsterdam : North-Holland Pub. Co., 1970, c1969  xxii, 542 p ; 25 cm
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8.

図書
図書
8. Statistical techniques in simulation (pt. 1 ; pt. 2)
Jack P.C. Kleijnen
出版情報: New York : M. Dekker, 1974-c1975  2 v. (xv, 775 p.) ; 24 cm
シリーズ名: Statistics : textbooks and monographs ; v. 9
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9.

図書
図書
9. Symposium on Monte Carlo methods : held at the University of Florida, conducted by the Statistical Laboratory, sponsored by Wright Air Development Center of the Air Research and Development Command, March 16 and 17, 1954
edited by Herbert Albert Meyer
出版情報: New York : Wiley, c1956  xvi, 382 p. ; 28 cm
シリーズ名: Wiley publications in statistics ; . Applied statistics
A Wiley publication in applied statistics
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10.

図書
図書
10. Monte Carlo methods in boundary value problems (: Berlin ; : New York)
Karl K. Sabelfeld
出版情報: Berlin ; Tokyo : Springer-Verlag, c1991  xii, 283 p. ; 25 cm
シリーズ名: Springer series in computational physics
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