Wavelet-based estimation of conditional densities using FlexCode method

• Grant number: 23/05587-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2023
• End date: May 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Statistics
• Principal Investigator: Michel Helcias Montoril
• Grantee: Vagner Silva Santos
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 18/04654-9 - Time series, wavelets and high dimensional data, AP.TEM

Abstract

This project involves the estimation of conditional densities using wavelet bases. The proposed approach, which is a wavelet-based version of the FlexCode method proposed by Izbicki and Lee [Converting high-dimensional regression to high-dimensional conditional density estimation. Electronic Journal of Statistics, 11(2): 2800--2831 (2017)], may help to solve the problem of estimating conditional densities in high dimensions, which is a significant challenge in statistical modeling. Conducting numerical studies to evaluate the quality of this proposal is a crucial part of this project. These studies can help validate the proposed approach and understand how it compares to other techniques for estimating conditional densities, such as the Fourier series-based version used originally in FlexCode.