Multivariate wavelet-based shape preserving estimation for dependent observations

Cosma, A.;Scaillet, Olivier;von Sachs, Rainer
(2005) , 34 pages

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Authors
  • Cosma, A.University of Lugano
    Author
  • Scaillet, OlivierHEC Genève
    Author
  • von Sachs, RainerUCLouvain
    Author
Abstract
We present a new approach on shape preserving estimation of probability distribution and density functions using wavelet methodology for multivariate dependent data. Our estimators preserve shape constraints such as monotonicity, positivity and integration to one, and allow for low spatial regularity of the underlying functions. As important application, we discuss conditional quantile estimation for financial time series data. We show that our methodology can be easily implemented with B-splines, and performs well in a finite sample situation, through Monte Carlo simulations
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Cosma, A., Scaillet, O., & von Sachs, R. (2005). Multivariate wavelet-based shape preserving estimation for dependent observations (STAT Discussion Paper 0516). https://hdl.handle.net/2078.5/33502