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課程資訊 |
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課程名稱 |
高等統計推論二 Advanced Statistical Inference (Ⅱ) | ||||||||||||||||||||
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開課學期 |
107-2 | ||||||||||||||||||||
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授課對象 |
社會科學院 經濟學系 | ||||||||||||||||||||
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授課教師 |
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課號 |
ECON5089 | ||||||||||||||||||||
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課程識別碼 |
323 U1960 | ||||||||||||||||||||
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班次 |
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學分 |
3.0 | ||||||||||||||||||||
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全/半年 |
半年 | ||||||||||||||||||||
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必/選修 |
選修 | ||||||||||||||||||||
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上課時間 |
星期一5(12:20~13:10)星期四8,9(15:30~17:20) | ||||||||||||||||||||
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上課地點 |
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備註 |
上課教室及資訊依課號MATH7604訊息為主。限選修ECON課號之課程，方可 限學士班三年級以上 或 限碩士班以上 總人數上限：20人 | ||||||||||||||||||||
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1072ECON5089_ | ||||||||||||||||||||
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 | ||||||||||||||||||||
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課程大綱
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課程概述 |
Contents:
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課程目標 |
The objective of this course is to introduce to the students of theory of inference including estimation, interval estimation and hypothesis testing. Both small and large sample theorems of hypothesis testing, interval estimation, and confidence intervals will cover. Applications to topics such as exponential families, linear models and nonparametric inference will be discussed.
It also provides a necessary basis for students for a further study of other advanced statistical courses. | ||||||||||||||||||||
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課程要求 |
Advanced statistical inference (I) or equivalent. Please refer to course webpage at ceiba.ntu.edu.tw on advanced Statistical Inference I (1001ASI)
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預期每週課後學習時數 |
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Office Hours |
每週四 14:00~15:00 每週一 13:20~14:20 備註： 週一、週四 授課老師 (天文數學大樓465室) ; 週一1:20-2:20PM、週四14:00-15:00、週五3-5PM 助 教 (天文數學館543室) | ||||||||||||||||||||
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指定閱讀 |
待補 | ||||||||||||||||||||
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參考書目 |
Textbook and References:
1. Casella, G. and Berger, R. L. (2002). Statistical Inference. 2nd ed. Duxbury Press. (Textbook) 2. Rice, J.A. (1995). Mathematical Statistics and Data Analysis. 2nd edition. Duxbury Press. 3. Bickel, P. S. and Doksum, K. A. (2001). Mathematical Statistics: Basic Ideas and Selected Topics, Vol. I, 2nd ed. Prentice Hall. 4. Lehmann, E. L. and Casella, G. (1998). Theory of Point Estimation. 2nd Edition, Springer. 5. Karr, A. F. (1993). Probability. Springer-Verlag. | ||||||||||||||||||||
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評量方式 (僅供參考) |
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課程進度 |
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週次 |
日期 |
單元主題 |
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第1週 |
Review on UMVUE and method based on a sufficient and complete statistic. Point Estimation. Information bound and systematic procedure of finding UMVUE. (constrained optimization problem) | |
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第2週 |
extreme value distributions and order statistics, probability inequality, method of mle with many parameters in Euclidean space, Bayesian point estimation and information integration | |
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第3週 |
continuous | |
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第4週 |
classical statistical inference: mle with finitely many parameters in Euclidean space | |
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第5週 |
MLE: consistency and asymptotic normality under compactness parameter space, Bayes estimate (l1 and l2 penalties, lasso versus ridge), Bayes estimate | |
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第6週 |
Quiz, MLE: consistency and asymptotic normality under compactness assumption (part 2) | |
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第7週 |
Incomplete data: MCAR, MAR, Truncation; EM algorithm, Introduction of Bayes estimate, regularization. no class on 4/04 | |
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第8週 |
Monday: review; Thursday: midterm | |
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第9週 |
自主學習週 | |
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第10週 |
Test of hypothesis: Framework, Neyman-Pearson lemma, Likelihood ratio test, | |
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第11週 |
Wald test, and Score test (asymptotic distribution) , large sample test | |
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第12週 |
Multi-normial distribution with large number of cells (Teaching model: histogram, kernel smoothing) | |
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第13週 |
continue | |
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第14週 |
Quiz 2 (5/20), Interval estimation and interpretation of confidence interval | |
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第15週 |
GLM: generalized linear model and logistic regression model | |
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第16週 |
Wrap up classical statistical estimation. | |
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第17週 |
Topics: smoothing techniques for curve fitting | |
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第18週 |
Monday: office hour, 期末考 final exam |