Some results in finding a lower bound of the efficiency of least square estimates relative to best linear estimates in regression model

IIMA Institutional Repository

Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/1297

Full metadata record

DC Field	Value	Language
dc.contributor.author	Raghavachari, M.	-
dc.date.accessioned	2010-03-15T04:32:48Z	-
dc.date.available	2010-03-15T04:32:48Z	-
dc.date.copyright	1974-12	-
dc.date.issued	2010-03-15T04:32:48Z	-
dc.identifier.uri	http://hdl.handle.net/11718/1297	-
dc.description.abstract	Consider the usual regression model Y = X? + ?. The standard estimators of ? are (i) Least squares estimator and (ii) Best linear estimator. The paper gives some results on finding an attainable lower bound on the efficiency of least square estimates relative to the best linear estimate. Specifically the paper is an attempt to verify the validity of a conjecture made by G.S. Watson. Consider the usual regression model Y = X? + ?. The standard estimators of ? are (i) Least squares estimator and (ii) Best linear estimator. The paper gives some results on finding an attainable lower bound on the efficiency of least square estimates relative to the best linear estimate. Specifically the paper is an attempt to verify the validity of a conjecture made by G.S. Watson.	en
dc.language.iso	en	en
dc.relation.ispartofseries	WP;1974/62	-
dc.subject	least square estimates	en
dc.subject	regression model	-
dc.title	Some results in finding a lower bound of the efficiency of least square estimates relative to best linear estimates in regression model	en
dc.type	Working Paper	en
Appears in Collections:	Working Papers

Files in This Item:

File	Description	Size	Format
WP 1974_62.pdf		350.62 kB	Adobe PDF	View/Open