Non- and Semiparametric Modelling (VL)
- Kategorie
- Master
- Lehrende(r)
- M. Müller, B. Cabrera-Lopez
Description
The course Non- and Semiparametric Modelling gives an overview over the flexible regression methods. The course starts with an introduction into the density estimation (histogram, kernel density estimation). Nonparametric regression methods and their applications are discussed. Furthermore additive models will be introduced in the course. At the end of the course the students will be able to implement methods to solve practical problems.Course Outline
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Introduction
Parametric Regression
Nonparametric Regression
Semiparametric Regression -
Nonparametric Density Estimation
Histogram, Average Shifted Histogram
Kernel Density Estimation (KDE) , Motivation and Derivation
KDE - Statistical Properties
KDE - Smoothing Parameter Selection
KDE - Choosing the Kernel
Confidence Intervals and Confidence Bands
Multivariate Kernel Density Estimation -
Nonparametric Regression
Univariate Kernel Regression
Other Smoothers (Regression Splines, Orthogonal Series)
Smoothing Parameter Selection
Confidence Regions and Tests
Multivariate Kernel Regression
Applications
Literature
- Härdle, Müller, Sperlich, Werwatz (2004): Non- and Semiparametric Modelling, Springer
- Fan, J. and Gijbels, I. (1996): Local Polynomial Modelling and Its Applications, Chapman and Hall, New York
- Härdle, W. (1990): Applied Nonparametric Regression, Econometric
- Society Monographs No. 19, Cambridge University Press
- Härdle, W. (1991): Smoothing Techniques, With Implementations in S, Springer, New York
- Härdle, Klinke, Müller (1999): XploRe - Academic Edition, The Interactive Statistical Computing Environment, Springer, New York
- Scott, D. W. (1992): Multivariate Density Estimation: Theory, Practice, and Visualization,
- John Wiley & Sons, New York, Chichester
- Silverman, B. W. (1986): Density Estimation for Statistics and Data Analysis, Vol. 26 of Monographs on Statistics and Applied Probability, Chapman and Hall, London
- Wand, M. P. and Jones, M. C. (1995): Kernel Smoothing, Chapman and Hall, London
- Yatchew, A., (2003): Semiparametric Regression for Applied Econometrician, Cambridge University Press, Cambridge
- Students can purchase the Professional Edition of XploRe and/or a bookset for a reduced price. For details please ask the lecturer or send an email to mdtech@mdtech.de.