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 seemsmore appropriated in my case, since I have the standard errorcalculated already (in terms of jumped distance) and it's interpretedas intraspecific variance due to sampling error. But when I make mymodel 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, butcouldn't find anything helpful to understand it.I'm attaching the first few lines of the prior V matrix. Thanks once again, DiogoEm 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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