Asymptotic efficiency of the OLSE for polynomial regression models with spatially correlated errors

Dong Wan Shin, Seuck Heun Song

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

For polynomial regression models with spatially correlated errors, the covariance matrix of the ordinary least-squares estimator (OLSE) is shown to have the same limiting value as that of the generalized least-squares estimator (GLSE) under the same normalization. This implies that the OLSE is asymptotically efficient.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalStatistics and Probability Letters
Volume47
Issue number1
DOIs
StatePublished - 15 Mar 2000

Keywords

  • Efficiency
  • GLSE
  • OLSE
  • Polynomial regression model
  • Spatial correlation

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