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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Copula estimation through wavelets

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Author(s):
Medina, Francyelle L. [1] ; Morettin, Pedro A. [2] ; Toloi, Clelia M. C. [2]
Total Authors: 3
Affiliation:
[1] Univ Fed Pernambuco, Dept Stat, BR-50740560 Recife, PE - Brazil
[2] Univ Sao Paulo, Dept Stat, BR-05508090 Sao Paulo - Brazil
Total Affiliations: 2
Document type: Journal article
Source: BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS; v. 34, n. 3, p. 439-463, AUG 2020.
Web of Science Citations: 0
Abstract

Recently some nonparametric estimation procedures have been proposed using kernels and wavelets to estimate the copula function. In this context, knowing that a copula function can be expanded in a wavelet basis, we propose a new nonparametric copula estimation procedure through wavelets for independent data and times series under an alpha-mixing condition. The main feature of this estimator is that we make no assumptions on the data distribution and there is no need to use ARMA-GARCH modelling before estimating the copula. Convergence rates for the estimator were computed, showing the estimator consistency. Some simulation studies are presented, as well as analysis of real data sets. (AU)

FAPESP's process: 13/00506-1 - Time series, wavelets and functional data analysis
Grantee:Pedro Alberto Morettin
Support Opportunities: Research Projects - Thematic Grants