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.
