Linear prediction sufficiency for new observations in the general Gauss-Markov model

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24 Citations (Scopus)

Abstract

We consider the prediction of new observations in a general Gauss-Markov model. We state the fundamental equations of the best linear unbiased prediction, BLUP, and consider some properties of the BLUP. Particularly, we focus on such linear statistics, which preserve enough information for obtaining the BLUP of new observations as a linear function of them. We call such statistics linearly prediction sufficient for new observations, and introduce some equivalent characterizations for this new concept.

Original languageEnglish
Pages (from-to)1011-1023
Number of pages13
JournalCommunications in Statistics - Theory and Methods
Volume35
Issue number6
DOIs
Publication statusPublished - 2006
Externally publishedYes
Publication typeA1 Journal article-refereed

Keywords

  • BLUE
  • BLUP
  • fundamental equations of the best linear unbiased prediction
  • Gauss-Markov model
  • linear prediction
  • linear prediction sufficiency
  • linear sufficiency
  • linear zero functions
  • UNBIASED PREDICTION
  • MATRIX

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