MX001 Introduction to Non-Parametric Functional Regression

Faculty of Science
Spring 2010
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
Frederic Ferraty (lecturer), prof. RNDr. Ivanka Horová, CSc. (deputy)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Contact Person: prof. RNDr. Ivanka Horová, CSc.
Course Enrolment Limitations
The course is offered to students of any study field.
Syllabus
  • I. Preliminaries
  • I.1 Almost complete convergence
  • I.2 Some useful exponential inequalities
  • II. Nonparametric functional regression
  • II.1 Functional variables and problematics
  • II.2 Basic definitions (functional variable, functional regression models, kernel estimator)
  • II.3 Some asymptotic properties
  • - rate of a.co. convergence
  • - uniform convergence
  • II.4 Recent advances
  • - bandwidth choice
  • - kNN estimator
  • - asymptotic normality, bootstrap, confidence intervals
  • III. Towards functional processes
  • III.1 Functional processes and prediction problems
  • III.2 Modelling dependence: alpha-mixing
  • III.3 Some asymptotic results
Language of instruction
English
Further Comments
Study Materials
The course is taught only once.
The course is taught: in blocks.
The course is also listed under the following terms Spring 2025.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/spring2010/MX001