Statistics 220 - Articles

Statistics 220 - Articles

Stat 221 Statistical Computing Lecture Notes

The following are the lecture notes from Statistics 221 taught Spring 2004.

Bayes History

Bayes T (1763). An Essay Towards Solving a Problem in the Doctrine of Chances. Philosophical Transactions 53: 370-418. PDF file. PDF file of reprint in Biometrika 45: 296-315.
Bellhouse DR (2004). The Reverend Thomas Bayes, FRS: A Biography to Celebrate the Tercenternary of His Birth. Statistical Science 19: 3-43. PDF file.
Stigler SM (1983). Who Discovered Bayes's Theorem? American Statistician 37: 290-296. PDF file.

Examples of Bayesian Analyses

Berliner LM, Wikle CK , and Cressie N (2000). Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling. Journal of Climate, 13: 3953-3968. PDF file.
Berliner LM (2000). Hierarchical Bayesian Modeling in the Environmental Sciences. Allgemeines Statistisches Archiv, Journal of the German Statistical Society 84: 141-153.
Clark JS (2005). Why Environmental Scientists are Becoming Bayesians. Ecology Letters 8: 2-14. PDF file.
McMillan N, Bortnick SM, Irwin ME, and Berliner LM (2005). A Hierarchical Bayesian Model to Estimate and Forecast Ozone Through Space and Time. Atmospheric Environment 39: 1373-1382. PDF file
Shermer M (2004). God's Number Is Up. Scientific American, July 2004: 46. PDF file. Note that there is a typo in Shermer's calculations. The last sentence of the second to last paragraph should have read
I estimate the probability that God exists is 0.0002, or 0.02 percent.

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.