Broadband semi-parametric estimation of long-memory time series by fractional exponential models

Masaki Narukawa, Yasumasa Matsuda

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This article proposes broadband semi-parametric estimation of a long-memory parameter by fractional exponential (FEXP) models. We construct the truncated Whittle likelihood based on FEXP models in a semi-parametric setting to estimate the parameter and show that the proposed estimator is more efficient than the FEXP estimator by Moulines and Soulier (1999) in linear processes. A Monte Carlo simulation suggests that the proposed estimation is more preferable than the existing broadband semi-parametric estimation.

Original languageEnglish
Pages (from-to)175-193
Number of pages19
JournalJournal of Time Series Analysis
Volume32
Issue number2
DOIs
Publication statusPublished - Mar 1 2011

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Keywords

  • Fractional exponential models
  • Long-range dependence
  • Semi-parametric estimation
  • Whittle likelihood

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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