[R-sig-ME] Are BLUP from two different random factors independant ?
Thierry Onkelinx
thierry@onkelinx @ending from inbo@be
Tue Nov 27 09:59:21 CET 2018
Dear Stephane,
Why not simply fit a model without [[variety x network]]. Then IMHO [[variety
x year x network]] would be an estimate of sum you're interested in.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be
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<https://www.inbo.be>
Op di 27 nov. 2018 om 09:53 schreef LASSALVY Stephane <
stephane.lassalvy using geves.fr>:
> Hello all,
> I am encountering a question related to linear combination of the
> estimations of random effects with the Asreml-R package. I am considering
> the problem of getting the sum of two BLUP. I only want to make the sum of
> two random effects.
>
> My team and I, we are modelling over the years and over networks field
> trials data. The number of years which we use for an analysis is usually 2
> and the number of networks is 3.
>
> The model which we use is :
> Yield = intercept + year + network + year x network + year x network x
> trial + [[variety]] + [[variety x network]] + [[variety x year x network]]
> + [[variety x year x network x trial]] + [[error term ]]
>
> Year, network, year x network are fixed effects. The terms between
> brackets [[ ]] are random terms so we can compute BLUP.
>
> We get the estimation of random terms for single random terms with the
> summary.asreml command with the all = TRUE option.
>
>
> 1. Would you know a mean to compute the sum of two random terms
> estimations ? We are mostly interested in computing the sum of a BLUP
> "variety x network" and the related BLUPs for the "variety x year x
> network" term to get the estimation of the variety x network interaction
> for each year of trial. Computing the sum of the estimations is not so
> difficult, but I am not sure that we will be able to compute the standard
> error for such a sum. Therefore, if a function like predict is able to
> compute this sum, it would be a very good news for us.
>
>
>
> 1. In case I would have to do the calculation by myself, can I consider
> that, as the random factors [[variety x network]] and [[variety x year x
> network]] are independent, for a given variety, BLUP(variety x network) and
> BLUP(variety x year x network) ?
>
> Best regards,
> Stephane
>
> Stéphane LASSALVY
> GEVES La Valette
> 711, rue Jean-François Breton
> F-34090 Montpellier
> Tél. +33 (0)4 67 04 35 81
> Email : stephane.lassalvy using geves.fr<mailto:contact using geves.fr>
>
>
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