Optimality of block designs used in one way elimination of heterogeneity

Somy Kuriakose

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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/5159

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DC Field	Value	Language
dc.contributor.advisor	Krishnan, S	-
dc.contributor.author	Somy Kuriakose	-
dc.date.accessioned	2019-05-23T08:32:29Z	-
dc.date.available	2019-05-23T08:32:29Z	-
dc.date.issued	1995	-
dc.identifier.citation	170614	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/5159	-
dc.description	PG	en_US
dc.description.abstract	Block designs are usually used in experiments where it is important to eliminate heterogeneity at least in one direction. From the class of designs it is desired to choose a design which will estimate the elementary treatment contrasts with maximum precision. The optimality criteria are based on the dispersion matrix of all possible elementary contrasts. The A-optimality criterion based on the information matrix was derived. Usually for comparing test treatments with a control RBD is used with the control treatment replicated in all blocks. The same objective could be achieved by using Balanced Treatment Incomplete Block Designs (BTIBD). BTIBD was found to be more efficient than RBD with the control treatment replicated in all blocks. Optimalities of BTIBD were also examined. When a BTIBD was augumented with certain number of blocks, such that the augmented blocks contains only the test treatments the resulting design was found to be E-optimal.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Agricultural Statistics, College of Horticulture, Vellanikkara	en_US
dc.subject	Agricultural statistics	en_US
dc.subject	optimality	en_US
dc.subject	heterogeneity	en_US
dc.title	Optimality of block designs used in one way elimination of heterogeneity	en_US
dc.type	Thesis	en_US
Appears in Collections:	PG Thesis

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