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English

Multivariate wavelet-based shape preserving estimation for dependent observations

Collection
  • Cahiers de recherche; 2005.04
Publication date2005
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 nancial time series data. We show that our methodology can be easily implemented with B-splines, and performs well in a nite sample situation, through Monte Carlo simulations.

Keywords
  • Conditional quantile
  • Time series
  • Shape preserving wavelet estimation
  • B-splines
  • Multivariate process
Citation (ISO format)
COSMA, Antonio, SCAILLET, Olivier, SACHS, Rainervon. Multivariate wavelet-based shape preserving estimation for dependent observations. 2005
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Report
accessLevelPublic
Identifiers
  • PID : unige:5760
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Technical informations

Creation04/15/2010 12:19:50 PM
First validation04/15/2010 12:19:50 PM
Update time03/14/2023 3:26:28 PM
Status update03/14/2023 3:26:28 PM
Last indexation05/02/2024 11:31:50 AM
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