Dear R users,
I am having a problem using forecast.Arima fuction. Here is the whole code:
d=scan("D:/Data.txt")
d
D=ts(data=d, start=1981,end=2012, frequency=1)
D
Time Series:
Start = 1981
End = 2012
Frequency = 1
[1] 384 403 427 450 499 550 575 615 640 680 702 730 760 790
[15] 790 830 870 871 906 920 968 1010 1060 1111 1165 1191 1217 1221
[29] 1089 1089 1090 1103
lnD=log(D)
lnD3=diff(lnD, differences=3)
adf.test(lnD3)
Augmented Dickey-Fuller Test
data: lnD3
Dickey-Fuller = -3.5315, Lag order = 3, p-value = 0.05795
alternative hypothesis: stationary
#########d parameter is determined by ADF test, which is 3#############
Now choosing p and q parameters
par(mfrow=c(2,1))
acf(lnD3, lag.max=20)
pacf(lnD3, lag.max=20)
######### from acf and pacf, p=2, q=1##############
Now fitting Arima
arima1=arima(lnD3, order=c(2,0,1))
arima1
Series: x
ARIMA(2,0,1) with non-zero mean
Coefficients:
ar1 ar2 ma1 intercept
-0.5189 -0.2033 -1.0000 -1e-04
s.e. 0.1806 0.1770 0.0993 5e-04
sigma^2 estimated as 0.00118: log likelihood=54.24
AIC=-100.48 AICc=-97.87 BIC=-93.64
####### Which looks good#########
Using auto.arima() to see what R have in mind
autoarima=auto.arima(lnD, d=3)
autoarima
Series: lnD
ARIMA(2,3,0)
Coefficients:
ar1 ar2
-1.0282 -0.5851
s.e. 0.1524 0.1560
sigma^2 estimated as 0.001731: log likelihood=50.37
AIC=-94.73 AICc=-93.77 BIC=-90.63
###### From AIC and BIC, I prefer arima1 instead of autoarima######
Now using forecast.Arima
forecastArima1=foreca.Arima(arima1, h=5)
*Warining message
Error in ts(x) : 'ts' object must have one or more observations*
But forecasting autoarima is no problem
forecastAutoArima=forecast.Arima(autoarima, h=5, c=(0.95))
forecastAutoArima
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
2013 7.084688 7.031373 7.138004 7.003150 7.166227
2014 7.167079 7.049206 7.284951 6.986808 7.347349
2015 7.285478 7.069813 7.501142 6.955648 7.615308
2016 7.443636 7.085484 7.801789 6.895890 7.991383
2017 7.618670 7.081729 8.155612 6.797489 8.439852
Why???? Is there a bug probelm with arima() function itself???
If anyone knows the problem, or shows me a right direction, I would really
appreciate it!!!
Many many thanks!!!
Chintemur Batur
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