Markov chain Monte Carlo in statistical mechanics: The problem of accuracy

Technometrics

Volumn 43, Issue 3, 2001, Pages 347-355

  Mignani, S ^a   Rosa, R ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Bootstrap; Dependent data; Error propagation; Ising model; Metropolis algorithm; Resampling method; Statistical errors

Indexed keywords

ALGORITHMS; ESTIMATION; MONTE CARLO METHODS; SAMPLING; STATISTICAL MECHANICS; STATISTICS;

BOOTSTRAP; DEPENDENT DATA; ERROR PROPAGATION; ISING MODEL; METROPOLIS ALGORITHM; STATISTICAL ERRORS;

MARKOV PROCESSES;

EID: 0035419752     PISSN: 00401706     EISSN: None     Source Type: Trade Journal    
DOI: 10.1198/004017001316975934     Document Type: Article

References (48)

1. Bayesian computation and stochastic systems
2. Introduction: Theory and 'technical' aspects of Monte Carlo simulations
3. Finite size scaling analysis of Ising model block distribution functions
4. Introduction
5. The use of subseries values for estimating the variance of a general statistic from a stationary sequence
6. Markov chain Monte Carlo convergence diagnostic: A comparative review
7. Computers and the theory of statistics: Thinking the unthinkable
8. Error estimates on averages of correlated data
9. Monte Carlo computations on the Ising lattice
10. Test of the Monte Carlo method: Fast simulation of a small Ising lattice
11. Inference from iterative simulation using multiple sequences
12. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images
13. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments
14. Practical Markov chain Monte Carlo
15. Estimation and optimization of functions
16. Hadronic coupling constants in lattice gauge theory
17. Metropolis method, Gaussian proposals, and antithetic variables
18. On blocking rules for the bootstrap with dependent data
19. Beitrag zur theorie des ferromagnetismus
20. The jackknife and the bootstrap for general stationary observations
21. Theoretical comparisons of block bootstrap methods
22. Moving blocks jackknife and bootstrap capture weak dependence
23. Statistical resampling for accuracy estimate in Monte Carlo renormalization group
24. Equations of state calculations by fast computing machine
25. The moving block bootstrap to assess the accuracy of statistical estimates in Ising model simulations
26. Statistical error methods in computer simulations
27. Dynamic properties of the Monte Carlo method in statistical mechanics
28. Regeneration in Markov chain samplers
29. Crystal statistics. I. A two-dimensional model with an order-disorder transition
30. Asymptotic and finite-sample correlations between OBM estimators
31. The stationary bootstrap
32. Batch size effects in the analysis of simulation output
33. Discussion on "Constrained Monte Carlo maximum likelihood for dependent data, " by C. J. Geyer and E. A. Thompson
34. Probability in dynamical systems
35. Over-relaxation methods for Monte Carlo simulations of quadratic and multiquadratic actions
36. Monte Carlo renormalization group and the three-dimensional Ising model
37. Monte Carlo studies of simple liquid models