Brian Cullis

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Modelling variance structures for multi-term effects • Until now G and R variance structures have been applied to a single term. • There are applications which require variance models to be applied to more than one term • Three (perhaps four - time permitting) examples will be considered to illustrate the (relatively) new syntax • the previous toy example, • random regressions with a twist, • competition modelling in field trials using the random treatment interference (R-TIM) model and • linear mixed models for partial compositing. VSN Applied Statistics Conference 2011 Modelling variance structures of multi-term effects
Syntax for multi-term variance models ASReml-R syntax random= ∼ str(form, vmodel) form model formula specifying a set of terms that have an associated variance model vmodel a formula object containing ASReml variance functions separated by the “:” operators presenting each component of the direct product variance model VSN Applied Statistics Conference 2011 Modelling variance structures of multi-term effects
Page 1 and 2: Modelling variance structures of mu
Page 3 and 4: Linear mixed model The model Let y
Page 5 and 6: R-structures General Framework •
Page 7 and 8: Separability Direct products in R-s
Page 9: Separability Direct products in G-s
Page 13 and 14: Multi-site toy example Recall: mult
Page 15 and 16: Salinity tolerance in bread wheat A
Page 17 and 18: Salinity tolerance in bread wheat P
Page 19 and 20: Salinity tolerance in bread wheat M
Page 21 and 22: Salinity tolerance in bread wheat M
Page 23 and 24: Competition modelling in sorghum pl
Page 37 and 38: Partial compositing example from Sm

Brian Cullis

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