A complete sufficient statistic for the linear model under normality and a singular covariance matrix

Assuming normality, a general form of a complete sutiicient statistic for the linear mode] having a singular covariance matrix is determined. The relationship between the complete sufficient statistic and some of the methods for determining best linear unbiased estimators given in the literature is...

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Veröffentlicht in:	Communications in statistics. Theory and methods 1978-01, Vol.7 (15), p.1465-1473
1. Verfasser:	Seely, Justus
Format:	Artikel
Sprache:	eng
Schlagworte:	BLUE complete suffcient statistic g-inverse matrix Gauss-Markov estimator maximum likelihood regression UMVUE
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	Assuming normality, a general form of a complete sutiicient statistic for the linear mode] having a singular covariance matrix is determined. The relationship between the complete sufficient statistic and some of the methods for determining best linear unbiased estimators given in the literature is also discussed.
ISSN:	0361-0926 1532-415X
DOI:	10.1080/03610927808827728