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)==i])))) --------------------------------> this gives me my data set l=final$l g=final$g model=arima0(l,order=c(2,0,2),xreg=g,method=("ML")) } I get warnings like: Call: arima0(x = l, order = c(2, 0, 2), xreg = g, method = ("ML")) Coefficients: ar1 ar2 ma1 ma2 intercept xreg 0.2549 -0.7722 -0.5586 0.3563 3e-04 0 s.e. 0.1072 0.0866 1.6725 0.2221 2e-04 NaN sigma^2 estimated as 3.921e-06: log likelihood = 311.72, aic = -609.44 Warning message: In sqrt(diag(x$var.coef)) : NaNs produced What does this output mean? How do I get rid of this and do my analysis properly? Any help is welcome. Thanks, Preetam -- Preetam Pal (+91)-9432212774 M-Stat 2nd Year, Room No. N-114 Statistics Division, C.V.Raman Hall Indian Statistical Institute, B.H.O.S. Kolkata. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.