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Hi, I want to fit the following model to my data: Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t i.e. it is an ARMA(2,2) with some additional regressors X and M. [Z_t's are the white noise variables] How do I find the estimates of the coefficients in R? And also I would like to know what technique R employs to find the estimates? Any help is appreciated. Thanks, Preetam --...

...me") # lm model m_lm <- lm(Petal.Length ~ Species, d) # Extract group means: aggregate(m_lm$model$Petal.Length, list(m_lm$model$Species), mean) # Extract group SDs: aggregate(m_lm$model$Petal.Length, list(m_lm$model$Species), sd) # Extract group Ns: table(m_lm$model$Species) # t.test model m_t <- t.test(d$Petal.Length[1:50], d$Petal.Length[51:100], var.equal = TRUE) # Extract group means: m_t$estimate # Extract group SDs: # Not available # Extract group Ns: # Not available Dr. Caspar J. van Lissa Assistant professor of developmental data science Utrecht University, dept. Methodology...

Hi all, I want to fit the following model to my data: Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t i.e. it is an ARMA(2,2) with some additional regressors X and M. [Z_t's are the white noise variables] So, I run the following code: for (i in 1:rep) { index=sample(4,15,replace=T) final<-do.call(rbind,lapply(index,function(i) get(as.character(levels[as.numeric(levels)=...

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