105年第1學期-6189 統計計算 課程資訊

課程分享

選課分析

本課程名額為 70人,已有11人選讀,尚餘名額59人。

評分方式

評分項目 配分比例 說明
Homework assignments 30
Midterm and/or Presentations 30
Final and/or Projects 40

授課教師

蘇俊隆

教育目標

Introducing some computational techniques and algorithms used by statistical researchers and practitioners 1. Monte Carlo Methods (Integration and Optimization) 2. Markov Chain Monte Carlo 3. Resampling Methods (Bootstrap, Jackknife, and Cross-Validaton) 4. Data Mining (Trees, Neural Networks, and Support Vector Machines)

課程資訊

參考書目

a. Monte Carlo Statistical Methods by Christian P. Robert & George Casella
b. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman
c. Statistical Computing by William J. Kennedy & James E. Gentle
d. Elements of Statistical Computing by Ronald A. Thisted
e. Bayesian Statistical Modeling by Peter Congdon
f. An Introduction to the Bootstrap by Bradley Efron and Robert J. Tibshirani
g. Simulation by Sheldon M. Ross
h. An Introduction to Statistical Learning With Application in R by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani