On 14-03-2012, at 13:00, sagarnikam123 wrote: > yes,but i want AIC value to calculate for below value, using frequency =1 in > ts() function >> t > -0.15264004 > 0.056076439 > -0.07276116 > -0.00917326 > -0.02069089 > -0.00416232 > -0.07225855 > -0.02654577 > -0.06131410 > -0.09380202 > 0.057414014 > -0.05239976 > 0.014397612 > 0.016145161 > -0.00670587 > 0.018696335 > 0.036943654 > -0.02450233 > 0.031161705 > 0.006513503 > -0.02892329 > -0.00831519 > -0.00877744 > -0.00634399 > -0.02612019 > -0.02531800 > -0.01435533 > 0.011148840 > -0.01893775 > 0.029859128 > 0.029878797 > -0.00125987 > 0.031404385 > 0.035127606 > -0.00191775 > 0.059797202 > -0.03268047 > -0.06026960 > -0.02216465 > -0.08145612 > -0.02772806 > -0.03171683 > -0.02842562 > -0.11807898 > -0.01457311 > -0.12612482 > 0.409631265 > -0.06375234 > > > in short, i want to know which is best model if i have this type of > vectors(t) 200,each having 400 observations at respective time i.e. > 1,2,3,4.....400 > You seem to be changing what you want. First you wanted seasonal decomposition, you got answers and now you've changed the goal(post).
Well my final answer is look at the forecast package. Maybe auto.arima is what you want. Berend ______________________________________________ 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.
