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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.)

Wavelet estimation of functional coefficient regression models

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Author(s):
Montoril, Michel H. [1] ; Morettin, Pedro A. [2] ; Chiann, Chang [2]
Total Authors: 3
Affiliation:
[1] Univ Fed Juiz de Fora, Inst Exact Sci, Dept Stat, Juiz De Fora - Brazil
[2] Univ Sao Paulo, Inst Math & Stat, Dept Stat, Sao Paulo - Brazil
Total Affiliations: 2
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING; v. 16, n. 1 JAN 2018.
Web of Science Citations: 0
Abstract

The area of nonlinear time series models has experienced a great development since the 1980s. Although there is a wide range of parametric nonlinear time series models, in general, we do not know if the postulated model is the most appropriated one for a specific data set. This situation highlights the importance of nonparametric models. An interesting nonparametric model to fit nonlinear time series is the well-known functional coefficient regression model. Nonparametric estimations by, e.g., local linear regression and splines, are developed in the literature. In this work, we study the estimation of such a model using wavelets. It is a proposal that takes into account both, classical and warped wavelets. We present the rates of convergence of the proposed estimators and carry out simulation studies to evaluate automatic procedures (among AIC, AICc and BIC) for selecting the coarsest and finest levels to be used during the estimation process. Moreover, we illustrate the methodology with an application to a real data set, where we also calculate multi-step-ahead forecasts and compare the results with other methods known in the literature. (AU)

FAPESP's process: 13/21273-5 - Estimation of semi-functional linear models by wavelets
Grantee:Michel Helcias Montoril
Support type: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 13/09035-1 - Regression models in functional data analysis
Grantee:Michel Helcias Montoril
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 08/51097-6 - Time Series, Dependence Analysis and Applications
Grantee:Pedro Alberto Morettin
Support type: Research Projects - Thematic Grants
FAPESP's process: 13/00506-1 - Time series, wavelets and functional data analysis
Grantee:Pedro Alberto Morettin
Support type: Research Projects - Thematic Grants
FAPESP's process: 09/09588-5 - Estimation of FAR models by wavelets
Grantee:Michel Helcias Montoril
Support type: Scholarships in Brazil - Doctorate