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Please help me in writing the R code for this problem. I've been solving this for 4 days. It was hard for me to solve it. It's a simulation problem in R. The problem is My true model is a normal mixture which is given as 0.5 N(-0.8,1) + 0.5 N(0.8,1). This model has two components. I will get a random sample of size 100 from this model. I will do this 300 times. That means, I will have

....1,100.1) b = c(1.1,1.1,1.1,100.1,1.1,1.1,1.1,100.1,1.1,1.1,1.,100.1,1.1,1.1,1.1,100.1,1.1,1.1,1.1,100.1,1.1,1.1,1.,100.1) K <-ts(cbind(a,b),start=c(1.1,1.1), names=c("a","b")) fit.bvar <- szbvar(K, p = 1, lambda0=0.6, lambda=0.1, lambda3=2, lambda4=0.25,lambda5=0,mu5=0, mu6=0, prior=0) y <- matrix(c(rep(0,8),c(1.10,1.10,1.10,100.1,1.10,1.10,1.0,100.10)),ncol=2) h <- hc.forecast(fit.bvar,y,nsteps=8,burnin=300, gibbs=500,exog=NULL)

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking