Nonparametric Statistics


For the exam, you have to learn everything that I will teach you during the semester (definitions, theorems, and proofs). All the questions will be related to the course.


During the first part of the course we will follow the following lecture notes:

Lecture notes (written by László Györfi)

Then I will use pages 77-91 of the following Hungarian lecture notes:

Lecture notes (written by László Ketskeméty and Mária Pintér)

My hand-written notes related to the Hungarian lecture notes above

Finally I will use Chapter 2 (written by László Györfi, György Ottucsák and András Urbán) of the following homepage:

Log-optimal portfolios

Sometimes I will supplement the material using the following sources:


A Distribution-Free Theory of Nonparametric Regression

A Probabilistic Theory of Pattern Recognition

Elements of Information Theory

For those who need to extend their knowledge of probability, I recommend the book "Probability: Theory and Example" written by Rick Durrett. Note that the book gives also a short introduction into measure theory. It can be downloaded from the author's homepage:

Homepage of Rick Durrett