Spectral estimation in the presence of missing data

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Abstract

In this article we propose a quasi-Whittle estimator for parametric families of time series models in the presence of missing data. This estimator extends results to the incompletely observed case. This extension is valid to non-Gaussian and nonlinear models. It also allows us to bound the variance of an associated quasiperi-odogram. A simulation study empirically validates the proposed estimate for mixing and nonmixing models.

Original languageEnglish
Pages (from-to)59-79
Number of pages21
JournalTheory of Probability and Mathematical Statistics
Volume95
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Auto correlation
  • Limit theorems
  • Time series
  • Weakly dependent
  • Whittle estimator

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