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Lecturer(s)
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Hron Karel, prof. RNDr. Ph.D.
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Course content
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Exploratory multivariate statistics 1. Robust statistics (univariate and multivariate, robust regression) 2. Principal component analysis 3. Factor analysis 4. Cluster analysis 5. Discrimination analysis 6. Models with latent variables: PLS regression and classification, three-way models Statistical learning: 1. Resampling methods 2. Variable selection and regularization in regression models 3. Nonlinear modelling 4. Descriptive statistics for functional data 5. Functional principal component analysis 6. Functional regression Time series analysis: 1. Adaptive approaches to modelling of trend in time series 2. Modelling of seasonality in time series 3. Basic models in the Box-Jenkins approach to time series modelling 4. Stationarity, autocorrelation and partial autocorrelation functions and their applications, modelling of nonstationar processes using the Box-Jenkins methodology
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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Realize contexture of basic conceptions and statements concerning exploratory multivariate statistics, statistical learning and time series analysis.
Synthesis Realize contexture of basic conceptions and statements concerning the course content.
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Prerequisites
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The student has to meet all prerequisites given for the study course Applied Mathematics and all the conditions of Study and Examination Regulations of the Palacký University in Olomouc.
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Assessment methods and criteria
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unspecified
The student has to understand the subject.
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Recommended literature
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