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Estimation of slowly time-varying trend function in long memory regression models

Lookup NU author(s): Professor Emilio Porcu

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Abstract

© 2018 Informa UK Limited, trading as Taylor & Francis Group. We study the asymptotic properties of the least-squares estimator for the trend function of a particular class of locally stationary models, which are defined by considering a smooth variation of the trend function. Additionally, errors are assumed to be realizations from a long-range dependent stationary Gaussian process. Our findings are then illustrated through Monte Carlo simulations.

Publication metadata

Author(s): Ferreira G, Pina N, Porcu E

Publication type: Article

Publication status: Published

Journal: Journal of Statistical Computation and Simulation

Year: 2018

Volume: 88

Issue: 10

Pages: 1903-1920

Online publication date: 02/05/2018

Acceptance date: 14/04/2018

ISSN (print): 0094-9655

ISSN (electronic): 1563-5163

Publisher: Taylor and Francis Ltd

URL: https://doi.org/10.1080/00949655.2018.1466141

DOI: 10.1080/00949655.2018.1466141

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