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|Title: ||Overview of Joint Regression Analysis|
|Authors: ||Pereira, Dulce|
|Keywords: ||Joint Regression Analysis|
L2 environmental indexes
Zig zag algorithm
|Issue Date: ||Jul-2007|
|Abstract: ||Joint Regression Analysis (JRA) has been widely used to compare
cultivars. In this technique a linear regression is adjusted per cultivar. The slope
of each regression measures the ability of the corresponding cultivar to answer
to variations in productivity. Presently we are manly interested in cultivars with
better responses to high productivity. To extend the application range of JRA to
connected series of designs in incomplete blocks, thus going beyond the classic
case of series of randomized blocks, we introduced the L2 environmental indexes.
Nowadays, comparison trials for cultivars are mainly ®-designs, which have in-
complete blocks. Moreover, the introduction of these indexes: enables the inte-
gration of JRA into the statistical inference for normal models; allows a better
approach to the study of speci¯c interactions. These interactions occur when a
cultivar behaves abnormally well or abnormally badly, for a (location , year) pair.
We will also, use JRA to obtain and update of lists of recommended cultivars.
Appropriate algorithms have been developed for the adjustments: the zig zag
algorithm and the double minimization algorithm.|
|Appears in Collections:||CIMA - Comunicações - Em Congressos Científicos Internacionais|
MAT - Comunicações - Em Congressos Científicos Internacionais
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