@article{b0b8a245718545808f41d117f68d49e4,
title = "Estimation of slowly time-varying trend function in long memory regression models",
abstract = "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.",
keywords = "Local stationary, long-range dependence, non-stationarity, time-varying models",
author = "Guillermo Ferreira and Nicolas Pi{\~n}a and Emilio Porcu",
note = "Funding Information: Guillermo Ferreira would like to express his thanks for the support from DIUC 215.014.024-1.0, established by the University of Concepci{\'o}n and Postdoctoral scholarship from Conicyt, Chile, 2014 (Folio 74150023). Emilio Porcu has been supported by Fondecyt Regular Project from the Ministry of Science and Education, Chile. Publisher Copyright: {\textcopyright} 2018 Informa UK Limited, trading as Taylor & Francis Group.",
year = "2018",
month = jul,
day = "3",
doi = "10.1080/00949655.2018.1466141",
language = "British English",
volume = "88",
pages = "1903--1920",
journal = "Journal of Statistical Computation and Simulation",
issn = "0094-9655",
publisher = "Taylor and Francis Ltd.",
number = "10",
}