Hi all, I was running the adf test in R. CODE 1: adf.test(data$LOSS) Augmented Dickey-Fuller Test data: data$LOSS Dickey-Fuller = -1.9864, Lag order = 2, p-value = 0.5775 alternative hypothesis: stationary CODE 2: adf.test(diff(diff(data$LOSS))) Augmented Dickey-Fuller Test data: diff(diff(data$LOSS)) Dickey-Fuller = -6.9287, Lag order = 2, p-value = 0.01 alternative hypothesis: stationary Is my interpretation correct: The original data( in code 1) is not stationary the twice differenced data (in code 2) is *stationary* and the order of the corresponding ARMA(p,q) model are *p=2* (as lag order in the output is 2) and *q=0*;.i.e. the *AR coefficients for X(t-1) and X(t-2) are significant*, while those of X(t-3) onwards are insignificant. Appreciate your help. 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]]
a) This looks like homework. The Posting Guide clearly indicates that this list is not for homework help. b) This is a statistics theory question that happens to use R, not an R question that happens to be about statistics. Also off-topic per the Posting Guide... there are other forums for stats questions. --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity. Preetam Pal <lordpreetam at gmail.com> wrote:>Hi all, > >I was running the adf test in R. > > >CODE 1: > >adf.test(data$LOSS) > > Augmented Dickey-Fuller Test > >data: data$LOSS >Dickey-Fuller = -1.9864, Lag order = 2, p-value = 0.5775 >alternative hypothesis: stationary > > >CODE 2: > adf.test(diff(diff(data$LOSS))) > > Augmented Dickey-Fuller Test > >data: diff(diff(data$LOSS)) >Dickey-Fuller = -6.9287, Lag order = 2, p-value = 0.01 >alternative hypothesis: stationary > > > >Is my interpretation correct: > >The original data( in code 1) is not stationary > >the twice differenced data (in code 2) is *stationary* and the order of >the >corresponding ARMA(p,q) model are *p=2* (as lag order in the output is >2) >and *q=0*;.i.e. the *AR coefficients for X(t-1) and X(t-2) are >significant*, >while those of X(t-3) onwards are insignificant. > > >Appreciate your help. >Thanks, >Preetam