The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence

Sankara N Sethuraman, I. V. Basawa

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A vector time series model with long-memory dependence is introduced. It is assumed that, at each time point, the observations are equi-correlated. The model is based on a fractionally differenced autoregressive process (long-memory) adjoined to a Gaussian sequence with constant autocorrelation. The maximum likelihood estimators for the parameters in the model are derived and their asymptotic distributions are obtained.

Original languageEnglish (US)
Pages (from-to)285-293
Number of pages9
JournalStatistics and Probability Letters
Volume31
Issue number4
StatePublished - Feb 1 1997

Fingerprint

Long Memory
Time Series Models
Maximum Likelihood Estimator
Asymptotic distribution
Autoregressive Process
Autocorrelation
Model
Time series models
Maximum likelihood estimator
Long memory
Observation
Autoregressive process

Keywords

  • Asymptotic inference
  • Long-memory dependence
  • Maximum likelihood estimation
  • Time series

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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