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1、课程内容提要课程编号： 02817100 开课学期： 周学时/总学时: 33 学分：3?课程名称：统计学研究专题之三-统计方法最新进展 任课教师：Yao Qiwei 英文名称： 教学方式： lectures 考试方式： 内容提要：The aim of this course is to teach students the cutting-edge statistical methodologies that reflect the exciting development of the subject in the modern computer age. The methods conce
2、rned are typically computationally intensive and are particularly powerful in analyzing large scale data sets with complex structure. The course is focused on methodology rather than theory. Students will gain hands-on experience in analysing both real and simulated data with S - a versatile languag
3、eand environment for statistical data analysis.The course will cover a subset of the topics listed below.1. Maximum likelihood estimation revisited: standard MLE, EM-algorithm, bootstrapping standard error and bias, distance between working model and truth, maximum likelihood under wrong models - qu
4、asi-MLE, choosing a working model - AIC.2. Bayesian methods and Markov chain Monte Carlo (MCMC): basic Bayes, composition Monte Carlo, importance sampling, rejection/acceptance algorithm, Gibbs sampler, Metropolis-Hastings algorithm.3. Empirical likelihood: empirical distribution, empirical likeliho
5、od of means, computation and boostrap calibration, empirical likelihood for random vectors and their functions, estimating equations.4. Modeling based on local fitting: global fitting versus local fitting - an illustration by example, splines, kernel methods and local likelihood, bias-variance trade
6、off, effective number of parameters, BIC, cross-validation, additive models, varying-coefficient linear models.5. Statistical learning: boosting, neural network, support vector machines.教材：None参考书：Owen, A.B. (2001). Empirical Likelihood. Chapman & Hall/CRC, London.Hastie, T., Tibshirani, R. and Frie
7、dman, J. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York.Pawitan, Y. (2001). In All Likelihood: Statistical Modelling and Inference Using Likelihood.Clarendon Press, Oxford.Tanner, M.A. (1996). Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions. Springer, New York.Venables, W.N. and Ripley, B.D. (2002). Modern Applied Statistics with S (4th edition). Springer, New York.注：每门课程都须填写此表。本表不够可加页。
