Robust parameter estimation for stationary processes by an exotic disparity from prediction problem

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

A new class of disparities from the point of view of prediction problem is proposed for minimum contrast estimation of spectral densities of stationary processes. We investigate asymptotic properties of the minimum contrast estimators based on the new disparities for stationary processes with both finite and infinite variance innovations. The relative efficiency and the robustness against randomly missing observations are shown in our numerical simulations.

Original languageEnglish
Pages (from-to)120-130
Number of pages11
JournalStatistics and Probability Letters
Volume129
DOIs
Publication statusPublished - 2017 Oct 1

Keywords

  • Asymptotic efficiency
  • Minimum contrast estimation
  • Prediction problem
  • Spectral density
  • Stationary process

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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