On a modelling environmental indexes
| dc.contributor.author | Pereira, Dulce | |
| dc.date.accessioned | 2008-06-03T11:59:36Z | |
| dc.date.available | 2008-06-03T11:59:36Z | |
| dc.date.issued | 2007-07 | |
| dc.description.abstract | The paper deals with the structuring the Genotype x Environmental Interaction in an analysis of series of experiments. The analysis of regression is one of the most appropriate methods in this problem. As in regression analysis we should have two sets of variables, one characterizing genotypes while the second characterizing environments. The so-called adjusted means for genotypes constitute usually observations of dependent variable. The problem is how to model the environmental indexes being the observation of independent variable. In the paper we examine two approaches to modelling the environmental indexes, one is based on so called adjusted means for environments while second method uses iterative (called zig zag) algorithm for estimation of considering indexes. | en |
| dc.format.extent | 111789 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.accesstype | restrito_ue | en |
| dc.identifier.authoremail | dgsp@uevora.pt | |
| dc.identifier.capitulo | On a modelling environmental indexes | en |
| dc.identifier.edicao | Proceedings of the 22nd International Workshop on Statistical Modelling | en |
| dc.identifier.isbn | 978-84-690-5943-2 | en |
| dc.identifier.location | Barcelona | en |
| dc.identifier.numpag | 4 pag | en |
| dc.identifier.sharewith | Este registo é para ser partilhado na comunidade CIMA-UE. | en |
| dc.identifier.uri | http://hdl.handle.net/10174/1209 | |
| dc.identifier.volume | 1 | en |
| dc.language.iso | eng | |
| dc.publisher | Institut d'Estadística de Catalunya, IDESCAT | en |
| dc.rights | restrictedAccess | en |
| dc.subject | Genotype indexes | en |
| dc.subject | Environmental indexes | en |
| dc.subject | Adjusted means | en |
| dc.subject | Genotype | en |
| dc.title | On a modelling environmental indexes | en |
| dc.type | bookPart | en |