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...2,5505,5573,5331,5355,6057,6055,6771,6669,6375,6666,6383,6118 ,5927,5750,5122,5398,5817,6163,6763,6835,6678,6821,6421,6338,6265,6291 ,5540,5822,6318,6268,7270,7096,6505,7039,6440,6446,6717,6320) YY=as.timeSeries(Y) adf.test(Y) adf.test(YY) ======== Output ==== > adf.test(Y) Augmented Dickey-Fuller Test data: Y Dickey-Fuller = -6.1661, Lag order = 5, p-value = 0.01 alternative hypothesis: stationary Warning message: In adf.test(Y) : p-value smaller than printed p-value > adf.test(YY) Augmented Dickey-Fuller Test data: YY Dickey-Fuller = 12.4944, Lag order = 5, p-val...

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 Tes...

R has a Dickey-Fuller Test implementation (adf.test) that tests for unit roots in an autoregressive process with a constant and linear trend. Is there a DF implementation that doesn't use the constant or trend? Thanks, Jake. -- View this message in context: http://www.nabble.com/Dickey-Fuller-Tests-with-...

Hi All , Could you please tell using which library ,Dickey-Fuller Test can be run? Thanks a lot __________________________________________________ [[alternative HTML version deleted]]

Short question: Is it possible to use statistical tests, like the Augmented Dickey-Fuller test, in functions with for-loops? If not, are there any alternative ways to scale measures? Detailed explanation: I am working with time-series, and I want to flag curves that are not stationary and which display pulses, trends, or level shifts. >df DATE ID VALUE2012-03-06...

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...

...25 5.26 5.26 5.26 5.26 5.26 5.26 5.26 5.27 [145] 5.27 5.26 5.27 5.27 5.28 5.29 5.29 5.29 5.29 5.30 5.30 5.30 5.31 5.31 5.31 5.32 5.32 5.33 [163] 5.33 Now I want to conduct a test for stationarity using ADF test : > adf.test((data[,1]), "stationary", 0) Augmented Dickey-Fuller Test data: (data[, 1]) Dickey-Fuller = -3.7351, Lag order = 0, p-value = 0.02394 alternative hypothesis: stationary But surprisingly it leads towards rejestion of NULL [p-value is less than 0.05], i.e. indicates a possible stationary series. However ploting a graph of actual data set...

Hi, While doing the adf test using ur.df ?price.df2=ur.df(y=log(price),type = "drift", selectlags="AIC") summary(price.df2)? It gives two values for ?value of test statistic is: -1.5992?? 2.32? one value is the t-test (or t-ratio), what is the other one? Please help. TIA Aditya

Hi all, I tried to do a Dickey Fuller test with R using adf.test with a time series of german stock prices. I have 10 stocks from 1985 to 2009 with monthly stock prices. So if you do the math I have 289 values for each stock. I tried to do the test for each stock alone and had the 289 values of my first stock listed in R. When...

...the output of the last test is displayed. How can I ensure that the function root(var) will run and display the output from all tests, and not just the last one? Thank you, b. root <- function(var) { #---Phillips-Perron PP.test(var, lshort = TRUE) PP.test(var, lshort = FALSE) #---Augmented Dickey-Fuller adf.test(var, alternative = "stationary", k = trunc((length(var)-1)^(1/3))) #---KPSS kpss.test(var, null = "Level", lshort = TRUE) kpss.test(var, null = "Trend", lshort = FALSE) }

Hello all, I tried to extract the p-value from adf.test in tseries; however, I got the error message such as > ht=adf.test(list.var$aa) > ht$p-value Error in ht$p - value : non-numeric argument to binary operator > ht Augmented Dickey-Fuller Test data: list.var$aa Dickey-Fuller = -2.3147, Lag order = 4, p-value = 0.4461 alternative hypothesis: stationary > ht$data [1] "list.var$aa" > ht$p-value Error in ht$p - value : non-numeric argument to binary operator > ht$p NULL I do not have problem extracting the...

I am confused by obtaining different results when testing for unit root when using different packages. I have 2625 price entries for which I want to determine whether they exhibit unit root. First I test using adf.test from tseries package by running: > adf.test(P, k=30) Augmented Dickey-Fuller Test data: P Dickey-Fuller = -4.685, Lag order = 30, p-value = 0.01 alternative hypothesis: stationary Warning message: In adf.test(P, k = 30) : p-value smaller than printed p-value But adf.test includes a time trend that I wan to omit, which I do not know if it is possible. Thus I have to...

Hello, How can an interative unit root test be implemented in R? More specifically, given a time series, I wish to perform the Dickey Fuller Test on a daily basis for say the last 100 observations. It would be interative in the sense that this test would be repeated each day for the last 100 observations. Given the daily Dickey Fuller estimates of delta for the autoregressive process d(Y(t)) = delta * Y(t-1) + u(t) , the si...

I'm analizing the Argentina stock market (merv) I download the data from yahoo library(tseries) Argentina <- get.hist.quote(instrument="^MERV","1996-10-08","2003-11-03", quote="Close") merv <- na.remove(log(Argentina)) I made the Augmented Dickey-Fuller test to analyse if merv have unit root: adf.test(merv,k=13) Dickey-Fuller = -1.4645, p-value = 0.805, merv have unit root than diff(merv,1) is stationary. Than I made Breushch-Pagan test to test if residuals are identically distributed: library(lmtest) bptest(merv[2:1730]~-1+merv[1:1729],~m...

...When I saw that the .bkf file was smaller (the next morning) that what a previous 'ls -l' showed (the night before) I cancelled the backup. Is this something that I should expect to be able to do? Backup my Windows laptop to a Samba share? I'd sure like to. Thanks. -Dan -- Dan A. Dickey ddickey@charter.net

Hi All, I'm new to R and am trying to run a unit root test on the vector "y" (a time series of inflation (i.e. changes in the Consumer Price Index quarter on quarter)). I've run the Augmented-Dickey-Fuller Test below (R's URCA package). It gives me an error that it cannot find the function ur.df unless I comment out the third last line of code (see below). I try to call the function via the following: test <- ur.df(y, type = "none", lags = 1) Am I doing this correctly? Wh...

I am not able to run Dickey-Fuller test. adf.test() function is not working. It is showing 'Error: could not find function "adf.test" Can any tell how to call "time series" library? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternativ...

...Could anyone tells me why? In EViews these two are the same and the results are close to my first case. Thanks! A complete log: > CPILD4UR1<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags =4) > summary(CPILD4UR1) ############################################### # Augmented Dickey-Fuller Test Unit Root Test # ############################################### Test regression drift Call: lm(formula = z.diff ~ z.lag.1 + 1 + z.diff.lag) Residuals: Min 1Q Median 3Q Max -2.43555 -0.63440 -0.03048 0.53522 2.84237 Coefficients: Estimate Std....

Hello to all- 1. When I run a regression which implements the augmented Dickey-Fuller test, I am confused about the names given to the regressors in the output. I understand what "xGE" stands for in a standard "lm" test involving an independent variable GE for instance, but if I lags and or differences are included in the model, what do the following &quot...

I have a question regarding the adf.test command in the tseries library. I have a vector of time series observations (2265 daily log prices for the OEX to be exact). I also have this same data in first-differenced form. I want to test both vectors individually for staionarity with an Augmented Dickey-Fuller test. I noticed when I use the adf.test command from the tseries library, the general regression command used incorporates a constant and a linear trend -- (trend "order" of 1, I presume). My specific questions are as follows: (1) is it possible to alter the function to use a reg...