[R-sig-ME] MCMCglmm update

[Jarrod Hadfield]

Sorry - not sure how the non Ascii text creeped in ...1) should read:

1) Antedependence structures.

Structured antedependence models can now be fitted using the new  
variance structure ante[]. The suffix [] takes a number, giving the  
order of the antedependence model (e.g ante1 and ante2 give first and  
second order antedependence models), and the number can be prefixed by  
a ‘c’ to hold all regression coefficients of the same order equal. The  
number can also be suffixed by a 'v' to hold all innovation variances  
equal. For example, antec2v has 3 parameters: a constant innovation  
variance, and two constant regression coefficients (one 1-lagged, and  
one 2-lagged).

Cheers,

Jarrod



Quoting Jarrod Hadfield <j.hadfield at ed.ac.uk> on Wed, 07 Oct 2015  
06:39:18 +0100:

> Hi,
>
> MCMCglmm has been updated to version 2.22. A lot of minor annoying  
> bugs have been fixed, but as far as I am aware no major bugs have  
> been found. Quite a bit of new functionality has been added:
>
> 1) Antedependence structures.
>
> Structured antedependence models can now be fitted using the new  
> variance structure ante[]. The suffix [] takes a number, giving the  
> order of the antedependence model (e.g ante1 and ante2 give first  
> and second order antedependence models), and the number can be  
> prefixed by a '€˜c'€™ to hold all regression  
> coefficients of the same order equal. The number can also be  
> suffixed by a 'v'€™ to hold all innovation variances  
> equal. For example, antec2v has 3 parameters: a constant innovation  
> variance, and two constant regression coefficients (one 1-lagged,  
> and one 2-lagged).
>
> Priors for antedependence structures allow priors to be placed  
> directly on the regression parameters via a beta.mu (a vector of  
> prior means) and a beta.V (a matrix of prior variances) element to  
> the prior list
>
> 2) Path analysis.
>
> Path analysis could be performed previously using the sir function,  
> but it was cumbersome and did not work if all response variables  
> were not Gaussian and completely observed. The path function is less  
> flexible than the sir function, but it is easier to use and works  
> with non-Gaussian data. Paths are allowed between observations  
> within the same residual block, and  path(cause, effect, k)  
> specifies which of the k variables affect each other. For example,  
> if a three-response model was fitted then
>
> cbind(a,b,c)~trait+path(1,2,3)+path(1,3,3), rcov=~us(trait):units
>
> then states that a[i] determines b[i] and c[i].
>
> 3) Simulate
>
> A simulate method now exists and can be used to simulate  
> observations from a  model defined by a MCMCglmm object.
>
> 4) Predict
>
> The predict method is now more complete and accepts new data
>
> 5)  Random effect - residual correlations
>
> Random effect - residual correlations can now be fitted by  
> specifying covu=TRUE in the prior specification for the residual  
> structure. The set of residuals defined by this structure are  
> allowed to covary with the random effects specified by the final  
> random effect structure. If the residual (co)variance matrix is of  
> dimension n, and the final random effect (co)variance matrix is of  
> dimension m, then the residual prior specification must be of  
> dimension n+m. The final random effect (co)variance matrix should  
> not have a prior specification.
>
> 6) Random effect Bradley-Terry models
>
> Bradley-Terry models without random effects could already be fitted  
> in previous versions by simply taking the difference between the two  
> opponents predictors (and potentially fixing the intercept at zero  
> if no order effects were modelled). Random effects can now be fitted  
> using the multimembership model formulation mm(opponent1-opponent2),  
> which now allows a `-' as well as the traditional `+'.
>
> Cheers,
>
> Jarrod
>
>
> -- 
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> Scotland, with registration number SC005336.
>
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>



-- 
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.