ARMA modelling with non-Gaussian innovations

Wai Keung LI, A. I. MCLEOD

Research output: Contribution to journalArticlespeer-review

43 Citations (Scopus)

Abstract

The problem of modelling time series driven by non-Gaussian innovations is considered. The asymptotic normality of the maximum likelihood estimator is established under some general conditions. The distribution of the residual autocorrelations is also obtained. This gives rise to a potentially useful goodness-of-fit statistic. Applications of the results to two important cases are discussed. Two real examples are considered. Copyright © 1988 Wiley Blackwell. All rights reserved
Original languageEnglish
Pages (from-to)155-168
JournalJournal of Time Series Analysis
Volume9
Issue number2
DOIs
Publication statusPublished - Mar 1988

Citation

Li, W. K., & McLeod, A. I. (1988). ARMA modelling with non-Gaussian innovations. Journal of Time Series Analysis, 9(2), 155-168. doi: 10.1111/j.1467-9892.1988.tb00461.x

Keywords

  • Autoregressive moving-average process
  • Maximum likelihood estimation
  • Non-Gaussian innovations
  • Residual autocorrelations

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