Nonparametric estimation of functional dynamic factor model

Martínez-Hernández, Israel and Gonzalo, Jesús and González-Farías, Graciela (2022) Nonparametric estimation of functional dynamic factor model. Journal of Nonparametric Statistics, 34 (4). pp. 895-916. ISSN 1048-5252

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Abstract

Data can be assumed to be continuous functions defined on an infinite-dimensional space for many phenomena. However, the infinite-dimensional data might be driven by a small number of latent variables. Hence, factor models are relevant for functional data. In this paper, we study functional factor models for time-dependent functional data. We propose nonparametric estimators under stationary and nonstationary processes. We obtain estimators that consider the time-dependence property. Specifically, we use the information contained in the covariances at different lags. We show that the proposed estimators are consistent. Through Monte Carlo simulations, we find that our methodology outperforms estimators based on functional principal components. We also apply our methodology to monthly yield curves. In general, the suitable integration of time-dependent information improves the estimation of the latent factors.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Nonparametric Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? functional cointegrationfunctional dynamic factor modelfunctional time seriesi(1) functional processlong-run covariance operatorstatistics and probabilitystatistics, probability and uncertainty ??
ID Code:
171470
Deposited By:
Deposited On:
08 Jun 2022 08:35
Refereed?:
Yes
Published?:
Published
Last Modified:
06 Nov 2024 19:10