search for: nitt

...V=diag(4)/4,n=4))) m1<-MCMCglmm(fixed=cbind(resp1,resp2,resp3) ~ trait:(expl1 + expl2+ expl3+ expl4+ expl5...)+trait-1, random=~us(trait):rand1+us(trait): rand1: rand2+us(trait): rand1: rand2: rand3, rcov=~us(trait):units,family=c("gaussian","gaussian","zapoisson"),nitt=20000,burnin=5000,thin=10,prior=prior,data=dat) However, for zero-altered models it is recommended in the MCMCglmm course notes to constrain over-dispersion to be the same for both processes (the zero-alteration and poisson process) by using a trait by unit interaction in the R-structure. Addition...

...2))) #model1 m1<-MCMCglmm(cbind(y1.logit,y2.logit) ~ trait:Ecotype - 1, random=~us(trait):animal, rcov=~us(trait):units, family=c("gaussian","gaussian"), prior=prior1, data=meandata, pedigree=meantree, nodes="TIPS", thin=100, nitt=150000, burnin=30000, verbose=F) #prior model2 prior2<-list(R = list(V = diag(2)*x, n=2)) #model2 m2<-MCMCglmm(cbind(reac.prob.logit,inert.prob.logit) ~ trait:Ecotype - 1, rcov=~us(trait):units, family=c("gaussian","gaussian"), prior=prior2, da...

...rcov = ~ us(trait):units, prior = list( R = list(fix=1, V=0.5 * (I + J), n = 4), G = list( G1 = list(V = diag(4), n = 4), G2 = list(V = diag(4), n = 4))), burnin = burn, nitt = iter, family = "multinomial5", data = data, pr=TRUE, pl=TRUE, DIC = TRUE, verbose = FALSE) And the summary of the main effects: post.mean l-95% CI u-95% CI eff.samp pMCMC traitOpp_teache...

...I've specified my model as follows: m3.random.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, random = ~ other + focal, prior = prior.m3, burnin = burn, nitt = iter, family =c("poisson","poisson","poisson","poisson","poisson"), data = data, pr=TRUE, pl=TRUE, DIC = TRUE, verbose = FALSE) The prior, prior.m3 is as fo...

...it):units, > prior = list( > R = list(fix=1, V=0.5 * (I + J), n = 4), > G = list( > G1 = list(V = diag(4), n = 4), > G2 = list(V = diag(4), n = 4))), > burnin = burn, > nitt = iter, > family = "multinomial5", > data = data, We have no way to debug this without the data. Perhaps you should contact the maintainer and in your message attach the data? maintainer('MCMCglmm') [1] "Jarrod Hadfield <j.hadfield at e...

...prior = list( > > R = list(fix=1, V=0.5 * (I + J), n = 4), > > G = list( > > G1 = list(V = diag(4), n = 4), > > G2 = list(V = diag(4), n = 4))), > > burnin = burn, > > nitt = iter, > > family = "multinomial5", > > data = data, > > We have no way to debug this without the data. Perhaps you should contact > the maintainer and in your message attach the data? > > maintainer('MCMCglmm') > [1] &qu...

...ollows: > > m3.random.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, > Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, > random = ~ other + focal, > prior = prior.m3, > burnin = burn, > nitt = iter, > family =c("poisson","poisson","poisson","poisson","poisson"), > data = data, > pr=TRUE, > pl=TRUE, > DIC = TRUE, > verbose = FALSE)...

Dear R users: I am using hierchical modeling for a response varible (ordinal) given by patients for each doctor. My MCMC run with MCMMCglmm ( thin=20,nitt=208000,burnin=24000, family='ordinal') still can't have all the parameters pass the GEWEKE diagnosis test. I am trying to find the reason for the slow convergence. Can the reason be 20 out of 50 doctors having 5 or less response (6 docs with 1 , 4 docs with 2,? 3 docs with 3, 4 docs...

...om.present.r <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, > > Enh_teacher, SocTol_teacher, Eval_teacher) ~ +present + r + trait -1, > > random = ~ other + focal, > > prior = prior.m3, > > burnin = burn, > > nitt = iter, > > family =c("poisson","poisson"," > poisson","poisson","poisson"), > > data = data, > > pr=TRUE, > > pl=TRUE, > > DIC = TRUE, >...

Dear all, Is there a command or low level instruction to disable the L2 cache in GPUs. Can a certain section of memory be defined as uncachable. Can you please point me the approach to do it. Thank you Vishwas -------------- next part -------------- An HTML attachment was scrubbed... URL: <https://lists.freedesktop.org/archives/nouveau/attachments/20161107/a1b678b7/attachment.html>

I am recieving a connection unexpectedly closed error while trying to sync a directory on two machines. Rsync is in my path on both machines. I am using ssh and I can connect to the server fine through ssh. I am using a vpn but have no problems connecting to any of the servers with it. This is the full error message I get: Remote Machine: Connection refused rsync: connection unexpectedly