cc-ed back to the list....
Some observations seem to have no sampling variation and so have a
residual variance of zero - which is not allowed, and doesn't make much
sense.
Cheers,
Jarrod
On 16/07/2017 00:16, Diogo B. Provete wrote:
Hi Jarrod,
I have tried all the suggestions for specifying the random effects.
However, your last suggestion of making the residual covariance seems
more appropriated in my case, since I have the standard error
calculated already (in terms of jumped distance) and it's interpreted
as intraspecific variance due to sampling error. But when I make my
model as:
model1<-MCMCglmm(mean_distance~type_arena*type_of_stimulus,
*random=~Species, rcov=~idh(units):units*, data=df_spe,
family="gaussian", ginverse = list(Especie=treeAinv), nodes="ALL",
prior=ve_priors, nitt=300000, burnin=25000, thin = 100, verbose=FALSE)
with priors:
ve_priors = list(R = list(V = diag(df_spe$se_distance^2), fix=1),
G=list(G1=list(V=1, nu=0.02)))
I get the following error message:
Error in priorformat(if (NOpriorG) { :
V is not positive definite for some prior$G/prior$R elements .
I tried to google it and looked at your course notes ch. 3 and 4, but
couldn't find anything helpful to understand it.
I'm attaching the first few lines of the prior V matrix.
Thanks once again,
Diogo
Em sex, 14 de jul de 2017 às 18:47, Diogo B. Provete
<dbprov...@gmail.com <mailto:dbprov...@gmail.com>> escreveu:
Dear Jarrod,
Thanks very much for the quick reply.
I'll try to implement the changes in the model.
Have a nice weekend,
Diogo
Em Sex, 14 de jul de 2017 17:48, Jarrod Hadfield
<j.hadfi...@ed.ac.uk <mailto:j.hadfi...@ed.ac.uk>> escreveu:
Hi Diogo,
First, your model1 is unlikely to be valid unless the residual
variance
happens to be 1. You should not fix it at one, and use a prior
like:
prior = list(R = list(V = 1, nu = 0.02), G=list(G1=list(V=1,
nu=0.02)))
Note that the residual variance (Ve) is the intra-specific
variance,
assumed constant over species, as in Lynch's h2/Pagels Lambda.
If you
have the standard error (se) of each observation you can also
allow
heterogeneity between observations as in random-effect
meta-analysis:
random=~Specie+idh(se)
If you fix the variance associated with se at 1 in the prior
prior = list(R = list(V = 1, nu = 0.02), G=list(G1=list(V=1,
nu=0.02), G2=list(V=1, fix=1)))
Then the intraspecific variance for species i is se^2_i+Ve
If you do not fix the variance associated with se at 1, for
example with
prior = list(R = list(V = 1, nu = 0.02), G=list(G1=list(V=1,
nu=0.02), G2=list(V=1, nu=0.02)))
and estimate the associated variance (Vse). Then the
intraspecific variance
for species i is Vse*se^2_i+Ve. This is useful if you only
know the standard error up to proportionality.
Alternatively you can fit fixed-effect meta-analysis where all
the intraspecific variance is presumed to be due to sampling
error:
random=~Specie, rcov=~idh(units):units
with prior:
prior = list(R = list(V = diag(se^2), fix=1),
G=list(G1=list(V=1, nu=0.02)))
The intraspecific variance for species i is se^2_i. This is
quite an inefficient way of doing fixed-effect meta-analysis,
and one day I will make such analyses easier to fit, and
quicker to fit......
Also, don't use nodes="TIPS" in the call to inverseA. I only
allowed this option because its the parameterisation used by
most other software, but its a really bad way of doing it.
Stick with the default, node="ALL".
Cheers,
Jarrod
On 14/07/2017 14:26, Diogo B. Provete wrote:
> treeAinv<-inverseA(phylo,nodes="TIPS",scale=TRUE)$Ainv
>
> I included the following priors:
>
> prior = list(R = list(V = 1, fix = 1), G=list(G1=list(V=1,
nu=0.02)))
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
--
*Diogo B. Provete, PhD.*
FAPESP Post-doctoral fellow
Department of Environmental Sciences
Centre for Sciences and Technologies for Sustainability
Federal University of São Carlos
Sorocaba
Gothenburg Global Biodiversity Centre
Box 462 SE-405 30
Göteborg, Sverige
diogoprovete.weebly.com <http://diogoprovete.weebly.com>
Cell phone: +5515981022137 <tel:%2815%29%2098102-2137>
Skype: diogoprovete
Editor: Amphibia-Reptilia | Biodiversity Data Journal
--
*Diogo B. Provete, PhD.*
FAPESP Post-doctoral fellow
Department of Environmental Sciences
Centre for Sciences and Technologies for Sustainability
Federal University of São Carlos
Sorocaba
Gothenburg Global Biodiversity Centre
Box 462 SE-405 30
Göteborg, Sverige
diogoprovete.weebly.com <http://diogoprovete.weebly.com>
Cell phone: +5515981022137 <tel:%2815%29%2098102-2137>
Skype: diogoprovete
Editor: Amphibia-Reptilia | Biodiversity Data Journal
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
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