PřF:MX001 Non-Parametric Func. Regr.

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

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, Spring 2026.