R help - Dec 2007 - time series tests

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

Citando pedrosmarques@portugalmail.pt:
> 
> Hi all,
> 
> Can anyone clear my doubts about what conclusions to take with the
following
> outputs 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
> 
> ______________________________________________
> 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.
> 

--

Hi all,

Can anyone clear my doubts about what conclusions to take with the following
outputs 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