Statistics 221 - Articles


Monte Carlo

  • Casella G and George EI (1992). Explaining the Gibbs Sampler. American Statistician 46: 167-174. PDF file.

  • Chib S and Greenberg E (1995). Understanding the Metropolis-Hastings Algorithm. American Statistician 49:327-335. PDF file.

  • Flury BD (1990). Acceptance-rejection Sampling Made Easy. Siam Review 32: 474-476. PDF file.

  • Hastings WK (1970). Monte Carlo Sampling Methods Using Markov Chains and Their Applications. Biometrika 1: 97-109. PDF file.

  • Irwin M, Cox N, and Kong A (1994). Sequential Imputation for Multilocus Linkage Analysis. Proceedings of the National Academy of Sciences of the USA 91: 11684-11688. PDF file.

  • Irwin ME, Cressie N, and Johannesson G (2002). Spatial-temporal nonlinear filtering based on hierarchical statistical models (with discussion). Test 11:249-302. PDF file.

  • Kong A, Liu JS, and Wong WH (1994). Sequential Imputations and Bayesian Missing Data Problems. JASA 89: 278-288. PDF file.

  • Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, and Teller E (1953). Equations of State Calculations by Fast Computings Machines. Journal of Chemical Physics 21: 1087-1092.

  • van der Merwe R, Doucet A, de Freitas N, and Wan E (2000). The Unscented Particle Filter. Technical Report CUED/F-INFENG/TR 380, Cambridge University Engineering Department. PDF file.

EM Algorithm and Extentions

  • Dempster AP, Laird NM, and Rubin DB (1977). Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society. Series B 38: 1-38. PDF file.

  • Louis TA (1982). Finding the Observed Information Matrix when Using the EM Algorithm. Journal of the Royal Statistical Society. Series B 44: 226-233. PDF file.

  • Meng XL and Rubin DB (1991). Using EM to Obtain Asymptotic Variance-Covariance Matrices: The SEM Algorithm. JASA 86: 899-909. PDF file.

  • Meng XL and Rubin DB (1993). Maximum Likelihood Estimation via the ECM Algorithm: A General Framework. Biometrika 80: 267-278. PDF file.

  • Wu CFJ (1983). On the Convergence Properties of the EM Algorithm. The Annals of Statistics 11:95-103. PDF file.

Harvard Statistics
Department of Statistics
Harvard University
Harvard University