PřF:M8CAO Bootstrap methods - Course Information
M8CAO Bootstrap methods for nonparametric curve estimation
Faculty of ScienceSpring 2011
- Extent and Intensity
- 2/0. 2 credit(s). Type of Completion: z (credit).
- Teacher(s)
- Ricardo Cao (lecturer), prof. RNDr. Ivanka Horová, CSc. (deputy)
- Guaranteed by
- prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance Mathematics (programme PřF, N-AM)
- Mathematical Biology (programme PřF, N-BI)
- Mathematical Modelling and Numeric Methods (programme PřF, N-MA)
- Mathematics - Economics (programme PřF, N-AM)
- Statistics and Data Analysis (programme PřF, N-AM)
- Course objectives
- This short course includes di¤erent bootstrap methods for inference in non- parametric curve estimation (mainly in nonparametric density and regression estimation). The problem of construction of nonparametric con…dence intervals and bands for the density and the regression function will be treated. The boot- strap method will be also used to provide bandwidth selectors in kernel density estimation. A brief list of issues to be treated follows.
- Syllabus
- 1 Introduction to nonparametric curve estima- tion
- 1.1 Nonparametric density estimation
- 1.2 Nonparametric regression estimation
- 2 Bootstrap methods for density estimation
- 2.1 Bootstrap approximation for the sampling distribution of the Parzen-Rosenblatt kernel estimator
- 2.2 Bootstrap methods for bandwith selection
- 3 Bootstrap methods for nonparametric regres- sion estimation as in an unconditional sense.
- 3.1 Asymptotic distribution of the Nadaraya-Watson es- timator
- 3.2 Plug-in approximation
- 3.3 Wild bootstrap
- 3.4 Smoothed bootstrap in the explanatory variable
- 3.5 Comparison of the methods
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught only once.
The course is taught: in blocks.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2011/M8CAO