|
課程名稱 |
統計計算
Statistical Computing |
|
開課學期 |
111-1 |
|
授課對象 |
理學院 統計與數據科學研究所 |
|
授課教師 |
陳裕庭 |
|
課號 |
STAT5007 |
|
課程識別碼 |
250 U0070 |
|
班次 |
|
|
學分 |
3.0 |
|
全/半年 |
半年 |
|
必/選修 |
必修 |
|
上課時間 |
星期二8,9,10(15:30~18:20) |
|
上課地點 |
新501 |
|
備註 |
所核心必修課程。
總人數上限：30人 |
|
|
|
|
課程簡介影片 |
|
|
核心能力關聯 |
核心能力與課程規劃關聯圖 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
1. Random number generation: inverse transformation method; rejection sampling; transformation methods.
2. Monte Carlo methods: Monte Carlo estimates; statistical inference; variance reduction.
3. Resampling methods: bootstrapping; jackknife resampling.
4. Markov Chain Monte Carlo (MCMC) methods: Metropolis-Hastings algorithm; Gibbs sampler.
5. EM algorithm. |
|
課程目標 |
This course aims to cover fundamental concepts in statistical computing and introduce different methods from both theoretical and practical aspects. On completion of this course, students should:
1. understand principles and methods of stochastic simulation;
2. be familiar with high-level computation software such as R or MATLAB;
3. be able to apply different Monte Carlo methods to solve problems. |
|
課程要求 |
Basic calculus, Linear algebra, Introductory statistics |
|
預期每週課後學習時數 |
|
|
Office Hours |
每週二 13:30~15:00 |
|
指定閱讀 |
待補 |
|
參考書目 |
Voss J. (2014) An Introduction to Statistical Computing - A Simulation based approach, Wiley.
Rizzo, M. L. (2019) Statistical computing with R, Chapman and Hall/CRC.
Givens, G. H., & Hoeting, J. A. (2012) Computational statistics, John Wiley & Sons. |
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
Mid-term |
30% |
|
2. |
Final |
40% |
|
3. |
Homework |
20% |
|
4. |
Class participation |
10% |
|
|
|
週次 |
日期 |
單元主題 |
|
第1週 |
9/6 |
Course introduction
Review of probability and statistics |
|
第2週 |
9/13 |
Random number generation |
|
第3週 |
9/20 |
Random number generation II |
|
第4週 |
9/27 |
Simulating statistical models |
|
第5週 |
10/4 |
Monte Carlo methods: estimates |
|
第6週 |
10/11 |
Monte Carlo methods: variance reduction methods |
|
第7週 |
10/18 |
Monte Carlo methods: applications to statistical inference |
|
第8週 |
10/25 |
Mid-term |
|
第9週 |
11/1 |
Bootstrapping: basic methods |
|
第10週 |
11/8 |
Bootstrapping: bootstrap inference |
|
第11週 |
11/15 |
No class (校慶) |
|
第12週 |
11/22 |
Markov Chain Monte Carlo methods |
|
第13週 |
11/29 |
Markov Chain Monte Carlo methods II |
|
第14週 |
12/6 |
EM algorithm |
|
第15週 |
12/13 |
EM variants |
|
第16週 |
12/20 |
Final |
|