Wavelets and estimation of long memory in nonstationary models: Does anything beat the exact local whittle estimator?. Issue 2 (7th February 2017)

• Record Type: Journal Article
• Authors: Boubaker, H.; Boutahar, M.; Khalfaoui, R.
• Is Part Of: Communications in statistics. Volume 46:Issue 2(2017)
• Page Start: 1189
• Page End: 1218
• Publication Date: 2017-02-07
• Subjects: Long memory -- Nonstationary models -- Wavelets; 91B84 -- 91B82 -- 91B84; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2014.995814
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: In this article, we analyze the performance of five estimation methods for the long memory parameter d . The goal of our article is to construct a wavelet estimate for the fractional differencing parameter in nonstationary long memory processes that dominate the well-known estimate of Shimotsu and Phillips(2005) . The simulation results show that the wavelet estimation method of Lee(2005) with several tapering techniques performs better under most cases in nonstationary long memory. The comparison is based on the empirical root mean squared error of each estimate.