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notes0.pdf | Lecture Notes part O | prof. RNDr. Ivan Mizera, CSc. |
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notes1.pdf | Lecture Notes part I | prof. RNDr. Ivan Mizera, CSc. |
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notes2.pdf | Lecture Notes part II | prof. RNDr. Ivan Mizera, CSc. |
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problems.pdf | Homework problems | prof. RNDr. Ivan Mizera, CSc. |
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An introduction to traditional and modern methods of multivariate statistics.
Last update: Omelka Marek, doc. Ing., Ph.D. (01.06.2023)
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Teach students basic methods of multivariate statistical analysis. Last update: Mizera Ivan, prof. RNDr., CSc. (15.10.2023)
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Requirements for obtaining the credit (zápočet): participation in the exercises (max 3 absences) and continual solving of the assigned problems (acquiring at least 36 credits, where one solved problem typically amount to one credit). The nature of these requirements precludes any possibility of additional attempts to obtain the class credit. Acquired credit is a condition for attending the examination, which will be in the written form, and apart from simple questions similar to those covered in the exercises will contain also questions regarding principles, motivations, algorithms, and applications of the techniques covered in the lectures. Last update: Mizera Ivan, prof. RNDr., CSc. (15.10.2023)
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Bouveyron C., Celeux G., Murphy T.B., Raftery A. E.: Model-based Clustering and Classification for Data Science: with Applications in R. Cambridge University Press, 2019.
Härdle, W. K., Hlávka, Z.: Multivariate Statistics: Exercises and Solutions, 2nd edition, Springer, 2015.
Härdle W. K., Simar L.: Applied Multivariate Statistical Analysis, 4th edition, Springer, 2015.
Mardia K.V., Kent J.T., Bibby J.M.: Multivariate Analysis. Academia Press. London, 1979.
Rao C.R.: Linear Statistical Inference and Its Applications. 2nd edition. Wiley. New York, 1973.
Venables W.N. Ripley B.D.: Modern Applied Statistics with S, 4th edition, Springer, 2002. Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (08.12.2020)
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Lecture+exercises. Last update: T_KPMS (16.05.2013)
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The exam will be in written form. Last update: Mizera Ivan, prof. RNDr., CSc. (03.10.2023)
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1. Multivariate normal distribution.
2. Wishart and Hotelling distribution.
3. Multivariate statistical inference.
4. Principal components and factor analysis.
5. Canonical correlations, correspondence analysis.
6. Discriminant and cluster analysis.
7. Projections-based methods, data depth.
8. Statistical software. Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (08.12.2020)
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basic knowledge of linear algebra, theory of probability, and mathematical statistics Last update: Hlávka Zdeněk, doc. RNDr., Ph.D. (25.05.2018)
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