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Parameter expansion with MCMCglmm
3 messages · Nate Fronk, Jarrod Hadfield
4 days later
Hi,
Is the error meassage
Error in priorformat(if (NOpriorG) { : V is the wrong dimension for
some prior$G/prior$R elements
or
Error in priorformat(if (NOpriorG) { : alpha.V is the wrong dimension
for some prior$G/prior$R elements
?
I think it should be the latter. If so alpha.V should be a 4x4 matrix
rather than a scalar, and alpha.mu should be a vector of length 4
rather than a scalar.
Cheers,
Jarrod.
Quoting Nate Fronk <nrf5017 at psu.edu> on Tue, 18 Jun 2013 15:04:30 -0400:
Hello all,
I am trying to analyze a Before-After Control-Impact experiment. However, my
model is not converging well and I am attempting to use a prior with
parameter
expansion. I'm using count data (birds per point), well pad density per unit
area, and time (1=before, 2=after).
prior<list(R=list(V=diag(1),nu=0.002),G=list(G1=list(V=diag(1),nu=0.002,alpha.mu=0,alpha.V=625),G2=list(V=diag(1),nu=0.002,alpha.mu=0,alpha.V=625),G3=list(V=diag(4),nu=0.002,alpha.mu=0,alpha.V=625)))
modelA<-MCMCglmm(Count~Density*Time,random=~ Block + Block:Point
+idh(1+Density*Time):Species,family="poisson",pr=TRUE,prior=prior,data=edge,nitt=40000)
When trying to use the prior I get the following message:
Error in priorformat(if (NOpriorG) { : V is the wrong dimension
for some prior$G/prior$R elements
I realize that my V= value may be wrong but I'm unsure about what
the value actually should be. Should I be using my covariance
matrix? Any help anyone could offer would be greatly appreciated.
Thank you,
Nate Fronk
Penn State University
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Hi,
Is the error message
Error in priorformat(if (NOpriorG) { : V is the wrong dimension for
some prior$G/prior$R elements
or
Error in priorformat(if (NOpriorG) { : alpha.V is the wrong dimension
for some prior$G/prior$R elements
?
I think it should be the latter. If so alpha.V should be a 4x4 matrix
rather than a scalar, and alpha.mu should be a vector of length 4
rather than a scalar.
Cheers,
Jarrod.
Quoting Nate Fronk <nrf5017 at psu.edu> on Tue, 18 Jun 2013 15:04:30 -0400:
Hello all,
I am trying to analyze a Before-After Control-Impact experiment. However, my
model is not converging well and I am attempting to use a prior with
parameter
expansion. I'm using count data (birds per point), well pad density per unit
area, and time (1=before, 2=after).
prior<list(R=list(V=diag(1),nu=0.002),G=list(G1=list(V=diag(1),nu=0.002,alpha.mu=0,alpha.V=625),G2=list(V=diag(1),nu=0.002,alpha.mu=0,alpha.V=625),G3=list(V=diag(4),nu=0.002,alpha.mu=0,alpha.V=625)))
modelA<-MCMCglmm(Count~Density*Time,random=~ Block + Block:Point
+idh(1+Density*Time):Species,family="poisson",pr=TRUE,prior=prior,data=edge,nitt=40000)
When trying to use the prior I get the following message:
Error in priorformat(if (NOpriorG) { : V is the wrong dimension
for some prior$G/prior$R elements
I realize that my V= value may be wrong but I'm unsure about what
the value actually should be. Should I be using my covariance
matrix? Any help anyone could offer would be greatly appreciated.
Thank you,
Nate Fronk
Penn State University
[[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.