Iterative and Non-iterative Simulation Algorithms
暂无分享,去创建一个
[1] Feller William,et al. An Introduction To Probability Theory And Its Applications , 1950 .
[2] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[3] A. Barker. Monte Carlo calculations of the radial distribution functions for a proton-electron plasma , 1965 .
[4] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[5] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] L. Tierney,et al. Accurate Approximations for Posterior Moments and Marginal Densities , 1986 .
[7] Donald B. Rubin,et al. Comment : A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest : The SIR Algorithm , 1987 .
[8] W. Wong,et al. The calculation of posterior distributions by data augmentation , 1987 .
[9] Adrian F. M. Smith,et al. Bayesian computation via the gibbs sampler and related markov chain monte carlo methods (with discus , 1993 .
[10] D. Rubin. Using the SIR algorithm to simulate posterior distributions , 1988 .
[11] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[12] S. E. Hills,et al. Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling , 1990 .
[13] Xiao-Li Meng,et al. Using EM to Obtain Asymptotic Variance-Covariance Matrices: The SEM Algorithm , 1991 .
[14] D. Rubin,et al. Inference from Iterative Simulation Using Multiple Sequences , 1992 .
[15] L. Tierney. Exploring Posterior Distributions Using Markov Chains , 1992 .
[16] D. Spiegelhalter,et al. Modelling Complexity: Applications of Gibbs Sampling in Medicine , 1993 .
[17] J. Besag,et al. Spatial Statistics and Bayesian Computation , 1993 .
[18] Jun S. Liu,et al. Sequential Imputations and Bayesian Missing Data Problems , 1994 .
[19] P. Atzberger. The Monte-Carlo Method , 2006 .
[20] D. Rubin,et al. A Single Series from the Gibbs Sampler Provides a False Sense of Security * , 2008 .