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Multivariate Analysis
¿cÂE¿³ (HENRY HORNG-SHING LU)
INSTITUTE OF STATISTICS, NATIONAL CHIAO TUNG UNIVERSITY
TEL: 03-5731870 EMAIL:
hslu@stat.nctu.edu.tw
WWW:
http://www.stat.nctu.edu.tw/misg/eindex.htm
¡@ Goals and Preparations:
This course is designed to introduce useful methods and many applications in multivariate
analysis of big data. The attendants may use any computation software to practice, such as
R/SPLUS, MATLAB, SAS, SPSS and so forth. If the programs are written by low level
languages, like C/C++, FORTRAN, JAVA, together with the other existing computation libraries,
such as the IMSL libraries, numerical recipes, and Hadoop, it will be highly encouraged!
Background courses of statistics are inevitable to understand the materials.
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¡@Course Outlines:
- Computation Software:
- Multivariate Normal Distributions and Generalizations:
- Clustering:
- Regression Methods:
- Classification:
- Dimension Reduction:
¡@Main References:
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Härdle, W. K., Simar, L. (2012), Applied Multivariate Statistical Analysis, 3rd ed.,
Springer, Berlin.
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Everitt, B., Hothorn, T. (2011), An Introduction to Applied Multivariate Analysis with
R, Springer, Berlin.
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Anderson, T. W. (2003), An Introduction to Multivariate Statistical Analysis, 3rd ed.,
Wiley, New York.
¡@Evaluation:
- Homework: 50%
- Final Report: 50%
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