Large sample inference for a multivariate linear model with autocorrelated errors

Sankara N Sethuraman, I. V. Basawa

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We consider a multivariate linear model with autocorrelated errors. The mean vector of the process is assumed to be linear in the time-trend parameter β and the within-group variation parameter γ. The least-squares estimators of β and γ, and the related estimators of the autoregressive parameter θ and the error covariance matrix Σ are derived and their asymptotic distributions are obtained. Large sample tests of H1:γ=0 and H2:β=0are derived and the limit distributions of the restricted least-squares estimators β̂H1 and γ̂H2 are obtained under H1 and H2, respectively.

Original languageEnglish (US)
Pages (from-to)187-204
Number of pages18
JournalJournal of Statistical Planning and Inference
Volume41
Issue number2
DOIs
StatePublished - Jan 1 1994

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Multivariate Linear Model
Least Squares Estimator
Covariance matrix
Limit Distribution
Asymptotic distribution
Estimator
Inference
Least squares estimator

Keywords

  • Multivariate linear model
  • asymptotic tests
  • autoregressive processes
  • growth curves
  • least-squares estimation
  • limit distributions

ASJC Scopus subject areas

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

Cite this

Large sample inference for a multivariate linear model with autocorrelated errors. / Sethuraman, Sankara N; Basawa, I. V.

In: Journal of Statistical Planning and Inference, Vol. 41, No. 2, 01.01.1994, p. 187-204.

Research output: Contribution to journalArticle

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