Analysis of field experiments by least-squares smoothing

Green, PJ; Jennison, C; Seheult, A

Analysis of field experiments by least-squares smoothing

Green, PJ

Jennison, C Seheult, A

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Publisher:: Blackwell Publ Ltd
Publication Type:: Journal Article
Citation:: Journal of The Royal Statistical Society Series B-methodological, 1985, 47 (2), pp. 299 - 315
Issue Date:: 1985-01

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Field	Value	Language
dc.contributor.author	Green, PJ https://orcid.org/0000-0002-4367-4756	en_US
dc.contributor.author	Jennison, C	en_US
dc.contributor.author	Seheult, A	en_US
dc.date.issued	1985-01	en_US
dc.identifier.citation	Journal of The Royal Statistical Society Series B-methodological, 1985, 47 (2), pp. 299 - 315	en_US
dc.identifier.issn	1369-7412	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14544
dc.description.abstract	Assuminga smooth trendp lus independente rrorm odel fort he environmentael ffects in the yields of a fieldp lot experiment,le ast squares smoothingm ethodsa re developed to estimate both the treatmente ffectsa nd the unknown trend. Treatmente stimates are closely related to those resultingf roma generalizedl east squares analysisi n which the covariance structuref or the environmentael ffectsh as a particularf orm.H owever, the main emphases are on the accuracy of treatmente stimatesu nder a fixed smooth trend plus error model and the exploratory power of the basic method to isolate trende ffectso f unknownf orm. Althought he detailed developmenti s for the one-dimensionalc ase, generalizations of the smoothness concept and extensions to two dimensions are also discussed. Application of the basic method is illustrated on three data sets and the results compared with other analyses.	en_US
dc.publisher	Blackwell Publ Ltd	en_US
dc.relation.ispartof	Journal of The Royal Statistical Society Series B-methodological	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Analysis of field experiments by least-squares smoothing	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	47	en_US
utslib.location.activity	ISI:A1985ATC2100014	en_US
utslib.for	0104 Statistics	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	1403 Econometrics	en_US
dc.location.activity	ISI:A1985ATC2100014	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	2	en_US
pubs.volume	47	en_US

Abstract:

Assuminga smooth trendp lus independente rrorm odel fort he environmentael ffects in the yields of a fieldp lot experiment,le ast squares smoothingm ethodsa re developed to estimate both the treatmente ffectsa nd the unknown trend. Treatmente stimates are closely related to those resultingf roma generalizedl east squares analysisi n which the covariance structuref or the environmentael ffectsh as a particularf orm.H owever, the main emphases are on the accuracy of treatmente stimatesu nder a fixed smooth trend plus error model and the exploratory power of the basic method to isolate trende ffectso f unknownf orm. Althought he detailed developmenti s for the one-dimensionalc ase, generalizations of the smoothness concept and extensions to two dimensions are also discussed. Application of the basic method is illustrated on three data sets and the results compared with other analyses.

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http://hdl.handle.net/10453/14544