similar to: tseries "adf.test"

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 "output" stand

Hello! I do not understand what is meant by: "aic" and "bic" follow a top-down strategy based on the Akaike's and Schwarz's information criteria in the datails to the ADF.test function. What does a "top-down strategy" mean? Probably the respective criterion is minimized and the mode vector contains the lag orders at which the criterion attains it

Hi, I am quite new to R and would appreciate some guidance, if possible. I have imported a csv file: spread <- read.csv("Spread.csv") I get the following error when I try to run adf.test: > adf.test(spread,alternative = c("stationary", "explosive"),0) Error in embed(y, k) : 'x' is not a vector or matrix Why is this? -- View this message in context:

this command is used in tseries adf.test(x, alternative = c("stationary", "explosive"), k = trunc((length(x)-1)^(1/3))) this command apply adf test on data given in x .here general equatiuon that is, equation with constant and trend is used.if i did not include constant or trend in the equation and run the command then how i can run this command in tseries.

Dear sir, I am a new user of R statistical package. I want to perform adf.test(augmented dickey fuller test), which packages I need to install in order to perform it. I am getting following message on my monitor. *x<-rnorm(1000) > adf.test(x) Error: could not find function "adf.test" *I am waiting for your response. Kamlesh Kumar. -- Kamlesh Kumar Appt. No. - QQ420,

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

Hello everybody, I've got a matrix called EUROPEDATA and I want to calculate the adf test statistic (part of the tseries package) on a rolling basis for window my.win on each column; i.e. each column of EUROPEDATA represents a particular variable; for the first column I calculate the adf test statistic for window my.win = 60 for example, roll forward one observation, calculate the adf

Hi, I am trying to test whether a series is return series stationary, but before proceeding I wanted to make sure I understand correctly how to use the adf.test function and interpret its output... Could you please let me know whether I am correct in my interpretations? ex: I take x such as I know it doesn't have a unit root, and is therefore stationary 1/ > x <- rnorm(1000) >

Hello! I am applying the ADF.test function from package uroot to a time series of data. When I apply the full test, incorporating drift and trend terms, the regressor estimate of the drift term is not significantly different from zero. So I apply the test to a model without drift term, with deterministic trend only. But then I always get the following error:

Hi, While doing the ADF test in R using the following command I am getting the error and the result.."> x.ct=ur.df(rev$REVENUE,start=1,end=length(rev$REVENUE),frequency=1) Error in ur.df(rev$REVENUE, start = 1, end = length(rev$REVENUE), frequency = 1) : unused argument(s) (start = 1, end = 4, frequency = 1) >

Dear all, How to do ADF test ¡¢KPSS¡¢ PP¡¢GLS test in R£¿ Thanks a lot ! [[alternative HTML version deleted]]

Dear List, I have multiple time series, all of which (excepting 1) have missing values. These run for ~30 years, with monthly sampling. I need to determine stationarity, and have tried to use the Augmented Dickey-Fuller test (adf.test), but this cannot handle missing values. The same problem occurs when attempting cross-correlation (ccf). Could someone please suggest any suitable functions in

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Hello, I am using the ur.df function from the {arca} package to run the augmented Dickey-Fuller unit root test on several time series. However; I do not understand the econometric interpretation of the the "phi1" and "phi2" test-statisitc which are output if you choose a "trend" or "drift" model. I looked at the source code for the function but I do not

Hi all, Hope you people do not feel irritated for repeatedly sending mail on Time series. Here I got another problem on the same, and hope I would get some answer from you. I have following dataset: data[,1] [1] 4.96 4.95 4.96 4.96 4.97 4.97 4.97 4.97 4.97 4.98 4.98 4.98 4.98 4.98 4.99 4.99 5.00 5.01 [19] 5.01 5.00 5.01 5.01 5.01 5.01 5.02 5.01 5.02 5.02 5.03 5.03 5.03

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]

Dear Community, For my masters thesis I need to perform a multivariate granger causality test. I have found a code for bivariate testing on this page (http://www.econ.uiuc.edu/~econ472/granger.R.txt), which I think would not be useful for the multivariate case. Does anybody know a code for a multivariate granger causality test. Thank you in advance. Best Regards -- View this message in context:

Hi R users! I've come across using kpss tests for time series analysis and i have a question that troubles me since i don't have much experience with time series and the mathematical part underlining it. x<-c(253, 252, 275, 275, 272, 254, 272, 252, 249, 300, 244, 258, 255, 285, 301, 278, 279, 304, 275, 276, 313, 292, 302, 322, 281, 298, 305, 295, 286, 327, 286, 270, 289, 293, 287,

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 http://shorewall.net/pub/shorewall/2.1/shorewall-2.1.5 ftp://shorewall.net/pub/shorewall/2.1/shorewall-2.1.5 This completes the implementation of Kernel 2.6 IPSEC support in Shorewall. Documentation is still minimal -- see the releasenotes and http://shorewall.net/IPSEC-2.6.html - -Tom - -- Tom Eastep \ Nothing is foolproof to a sufficiently

Fritz just put the updated tseries package to CRAN. I mainly removed (and corrected) code such that tseries fits together with package ts. New code is White's and Teraesvirta's tests for neglected non-linearity (also for the regression case). From the INDEX file: NelPlo Nelson-Plosser Macroeconomic Time Series adf.test Augmented Dickey-Fuller Test amif