Hi all,
Can anyone clear my doubts about what conclusions to take with the following
what puts of some time series tests:
> adf.test(melbmax)
Augmented Dickey-Fuller Test
data: melbmax
Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01
alternative hypothesis: stationary
Warning message:
p-value smaller than printed p-value in: adf.test(melbmax)
>adf.test(melbmax,k=0,alternative="stationary")
Augmented Dickey-Fuller Test
data: melbmax
Dickey-Fuller = -24.4069, Lag order = 0, p-value = 0.01
alternative hypothesis: stationary
Warning message:
p-value smaller than printed p-value in: adf.test(melbmax, k = 0, alternative =
"stationary")
> pp.test(melbmax,alternative="stationary")
Phillips-Perron Unit Root Test
data: melbmax
Dickey-Fuller Z(alpha) = -1124.030, Truncation lag parameter = 9,
p-value = 0.01
alternative hypothesis: stationary
Warning message:
p-value smaller than printed p-value in: pp.test(melbmax, alternative =
"stationary")
> Box.test(melbmax)
Box-Pierce test
data: melbmax
X-squared = 1893.093, df = 1, p-value < 2.2e-16
> Box.test(melbmax,type="Ljung-Box")
Box-Ljung test
data: melbmax
X-squared = 1894.650, df = 1, p-value < 2.2e-16
> kpss.test(melbmax)
KPSS Test for Level Stationarity
data: melbmax
KPSS Level = 0.1163, Truncation lag parameter = 13, p-value = 0.1
Warning message:
p-value greater than printed p-value in: kpss.test(melbmax)
> x=time(melbmax)
> y=as.vector(melbmax)
> melbmaxsaz=lowess(x,y,f=0.05)$y
> melbmaxtrend=lowess(x,y,f=0.5)$y
> melbmaxres=19.19+19.21+melbmax-ts(melbmaxsaz, start=1981,
> frequency=365)-ts(melbmaxtrend, start=1981, frequency=365)
> kpss.test(melbmaxres)
KPSS Test for Level Stationarity
data: melbmaxres
KPSS Level = 0.1322, Truncation lag parameter = 13, p-value = 0.1
Warning message:
p-value greater than printed p-value in: kpss.test(melbmaxres)
> kpss.test(melbmaxres,null="Trend")
KPSS Test for Trend Stationarity
data: melbmaxres
KPSS Trend = 0.1339, Truncation lag parameter = 13, p-value = 0.07243
Best regards
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