Jussi Klemelä

Jussi Klemelä
University of Oulu
Department of Mathematical Sciences
P.O. Box 3000
90014 University of Oulu, Finland

Email: jussi.klemela at oulu.fi
Phone: +358-8-553 1754
Fax: +358-8-553 1730
Office: Pentti Kaiteran katu 1, M219

Nonparametric function estimation

Teaching

• Kvantitatiivisen rahoituksen koulutusohjelma

• Ekonometrian tilastolliset perusteet, 805339A 805683S 721339S, Kevät 2012
• Aikasarja-analyysi, 805324A 805679S, Kevät 2012

Vanhoja kursseja

• Pitkittäis- ja paneeliaineistojen analysointi, 805308A 805646S, Syksy 2011
• Tilastollinen päättely II, 805611S, Kevät 2011
• Rahoituksen tilastotiede, 806628S, Syksy 2010
• Markkinariskin analyysi, 806330A, Syksy 2010
• Ekonometrian tilastolliset perusteet, 805339A, Kevät 2010
• Rahoituksen tilastotiede/Statistical finance, Syksy 2009
• Nonparametric function estimation with applications in finance, Kevät 2009

Book

The homepage of the book contains preview, blog, software, the figures, and advice to their reproduction.

Preprints

Software

• R-package "denpro" for the visualization of multivariate density estimates.


• R-package "delt" for the estimation of multivariate densities with adaptive histograms.


• R-package "finatool" for portfolio selection and pricing and hedging of options. (Under development)

Selected publications

• J. Klemelä and E. Mammen. (2010). Empirical risk minimization in inverse problems Ann. Statist. 38(1): 482-511.


• J. Klemelä. (2007). Visualization of multivariate data with tail trees. Information Visualization 6: 109-122.


• J. Klemelä. (2006). Sharp adaptive estimation of quadratic functionals. Probab. Theory Relat. Fields. 134(4): 539-564.


• J. Klemelä. (2004). Visualization of multivariate density estimates with level set trees. J. Comput. Graph. Statist. 13(3): 599-620.


• J. Klemelä and A. B. Tsybakov. (2001). Sharp adaptive estimation of linear functionals. Ann. Statist. 29: 1567-1600.

Animations

• Animations on density estimation
  • Growing of a level set tree tree
  • Growing of a shape tree
  • Growing of a tail tree
  • Slices of a function
  • CART visualization vs. level set tree visualization
• Animations on statistical finance
  • Scatter matrices
  • Scatter matrices; copula transformed data
  • Scatter matrices; original data
  • Hedging
  • Hedging with Gaussian asset prices
  • Hedging with Student asset prices
  • Hedging of an ATM option with Gaussian and Student asset prices
  • Profit distributions
  • Profit distributions of call options
  • Profit distributions of strangles
  • Profit distributions of condors
    • Movie I
    • Movie II

Talks

• Analysis of dependency with density estimation (PDF)
• Level set trees and the analysis of shapes (PDF)
• Likelihood subsetting of financial data (PDF)
• Empirical risk minimization in inverse problems (PDF)
• Density estimation with stagewise optimization of the empirical risk (PDF)
• Visualization of multivariate functions, sets, and data (PDF)
• Visualization of multivariate density estimates with shape trees (PDF)
• Visualization of multivariate density estimates (PDF)

Lectures on nonparametric function estimation

In nonparametric function estimation one approximates and interpolates functions when only noisy data is available. Functions to be estimated include probability density functions, regression functions, spectral density functions, and intensity functions. The lectures will concentrate on the estimation and visualization of multivariate density functions, but the techniques apply also to other kinds of functions. The estimation techniques include the use of anisotropic kernel estimators, minimization estimators, multivariate adaptive histograms, wavelet estimators, best basis selection, and stagewise minimization.

• Lecture I, 1.10.2007 (PDF)
• Lecture II, 15.10.2007 (PDF)
• Lecture III, 29.10.2007 (PDF)
• Lecture IV, 12.11.2007 (PDF)
• Lecture V, 26.11.2007 (PDF)
• Lecture VI, 10.12.2007 (PDF)