CDOoDocuments.StdDocumentDescDocuments.DocumentDescContainers.ViewDescViews.ViewDescStores.StoreDescP Documents.ModelDescContainers.ModelDescModels.ModelDescStores.ElemDesc TextViews.StdViewDescTextViews.ViewDesc@ TextModels.StdModelDescTextModels.ModelDescJ B TextModels.AttributesDesc1$Courier New $Courier New #------------------------------------------------------------------------------------------------------------------------------ model 4 #------------------------------------------------------------------------------------------------------------------------------ model{ C<-92.0 # model's likelihood for (i in 1:n){ time[i] ~ dnorm( mu[i], tau ) # stochastic componenent # link and linear predictor mu[i] <- beta[1] + beta[2] * cases[i] + beta[3] * distance[i] log.like[i] <- -0.5*log(2*3.14)-0.5*log(s2)-0.5*(time[i]-mu[i])*(time[i]-mu[i])/s2 } # prior distributions a<-0.001 b<-0.001 tau ~ dgamma( a,b) prior.prec <- 1.0E-3*tau beta[1] ~ dnorm( 0.0, prior.prec ) beta[2] ~ dnorm( 0.0, prior.prec ) beta[3] ~ dnorm( 0.0, prior.prec ) # definition of sigma s2<-1/tau s <-sqrt(s2) logs2<-log(s2) # inv.like <- exp( -sum(log.like[1:n]) -C ) for (k in 1:3){ log.prior[k]<- -0.5*log(2*3.14)+0.5*log(prior.prec)-0.5*pow( prior.prec*beta[k], 2) } log.prior[4] <- a*log(b)-loggam(a)+(a-1)*log(tau)-b*tau theta[1] <- beta[1] theta[2] <- beta[2] theta[3] <- beta[3] theta[4] <- tau for (k1 in 1:4){ for (k2 in 1:4){ g.sum[k1,k2] <- (theta[k1]-g.beta.mean[k1])*T[k1,k2]*(theta[k2]-g.beta.mean[k2]) }} log.g <- -0.5*4*log(2*3.14) + 0.5*logdet( T[1:4,1:4] ) -0.5*sum( g.sum[1:4,1:4] ) wlike <- exp(log.g -sum(log.like[1:n]) - sum(log.prior[1:4]) - C) } INITS list( tau=1, beta=c(0,0,0)) DATA (LIST) list( n=25, time = c(16.68, 11.5, 12.03, 14.88, 13.75, 18.11, 8, 17.83, 79.24, 21.5, 40.33, 21, 13.5, 19.75, 24, 29, 15.35, 19, 9.5, 35.1, 17.9, 52.32, 18.75, 19.83, 10.75), distance = c(560, 220, 340, 80, 150, 330, 110, 210, 1460, 605, 688, 215, 255, 462, 448, 776, 200, 132, 36, 770, 140, 810, 450, 635, 150), cases = c( 7, 3, 3, 4, 6, 7, 2, 7, 30, 5, 16, 10, 4, 6, 9, 10, 6, 7, 3, 17, 10, 26, 9, 8, 4) , g.beta.mean=c(2.38600,1.61300,0.01436,0.09371), T=structure(.Data=c(1.75421181591235, 14.0958842687956, 656.462859545804, -0.85592621385267, 14.0958842687956, 205.84463499194, 8863.06974370127, -17.3468007423018, 656.462859545804, 8863.06974370128, 456458.087860465, -484.618982434, -0.85592621385267, -17.3468007423018, -484.618982434, 1252.79180888501), .Dim = c(4, 4)) ) TextControllers.StdCtrlDescTextControllers.ControllerDescContainers.ControllerDescControllers.ControllerDesc TextRulers.StdRulerDescTextRulers.RulerDescTextRulers.StdStyleDescTextRulers.StyleDescZTextRulers.AttributesDesc$ ZGo * ,[ @Documents.ControllerDesc t]s ' `h*