ML estimation and an efficiency study for mean estimators in spatially correlated repeated arrays

Dong Wan Shin

Research output: Contribution to journalArticlepeer-review

Abstract

For spatially correlated repeated arrays, a simple method is proposed for maximum likelihood (ML) estimation of the mean parameters. Efficiency of the sample mean over the maximum likelihood estimator (MLE) is analyzed. Spatial correlations combined with heterogeneity of spatial correlations or heterogeneity of error variances are shown to have adverse effect on efficiency of the sample mean. Therefore, in such spatially correlated and heterogeneous situations, it is recommended that spatial correlations should be properly addressed in estimating mean parameters.

Original languageEnglish
Pages (from-to)47-52
Number of pages6
JournalJournal of the Korean Statistical Society
Volume38
Issue number1
DOIs
StatePublished - Mar 2009

Bibliographical note

Funding Information:
The authors are very grateful for two anonymous referees for their helpful comments. This work was supported by grant R01-2006-000-10563 from the Basic Research Program of the Korea Science & Engineering Foundation.

Keywords

  • 62F10
  • 62P10
  • Gene effects
  • Heterogeneity
  • Maximum likelihood estimator
  • Microarray
  • primary
  • secondary

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