similar to: urca package - summary method -

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,

Dear R-list member, an update of package 'urca' has been uploaded to CRAN (Mirror: Austria). In the updated release unit root and cointegration tests encountered in applied econometric analysis are implemented. The package is written in 'pure' R and utilises S4 classes. In particular, the Johansen procedure with likelihood ratio tests for the inclusion of a linear trend,

Sorry, to bother the list one more time: but the following worked at least for 'urca': in NAMESPACE I now included explicitly: import(methods) a fix of the 'urca'-package will be uploaded to CRAN on the weekend. Fritz, will this work for ypur package 'flexclust' too? I have in my DESCRIPTION imports: methods and in flexclust it is in depends: methods. However, both

Dear R-Devel subscriber, as a follow up to my yesterday's email: I tested an analogous example with the S4-package "flexclust" by executing the following code: library(flexclust) example(cclust) cl After saving the work space and starting a new R process with the restored work space, the same behaviour (i.e., the methods pertinent to "flexclust" are not used, even after

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

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)

Hi, Am I interpreting the results properly? Are my conclusions correct? > KPSS.test(df) ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null hypothesis of level stationarity: 1.089 Critical values: 0.10 0.05 0.025 0.01 0.347 0.463

is that 'x' is level or trend stationary. I did this > s<-rnorm(1000) > kpss.test(s) KPSS Test for Level Stationarity data: s KPSS Level = 0.0429, Truncation lag parameter = 7, p-value = 0.1 Warning message: p-value greater than printed p-value in: kpss.test(s) My question is whether p=0.1 is a good number to reject N0? On the other hand, I have a

I can't figure out how to get the "summary" method in the URCA package to work. E.g. when I use the following code fragment in the help for the "ca.jo" function, it always tries to use the "summary" method from the "base" package, not the "urca" package. How do I force it use the "summary" method of the "urca" package?

I'm trying to understand how to use kpss.test() properly. If I have a level stationary series like rnorm() in the help page, shouldn't I get a small p-value with the null hypothesis set to "Trend"? The (condensed) output from kpss.test() for the two possible null hypotheses is given below. I don't see any significant difference between these results. > x <-

Thank you Matthieu for your helpful suggestions. Unfortunately I still have problems. I have tried to compile it via your suggestion. " this is strange... you should have the usual summary... I have on my machine library(urca) test2<-ur.df(nottem, type="none", lags=1) summary(test2) " When I type in "library(urca)" I receive the following. "Error in

Dear Sir/Madam, I found your email address and your correspondence with R-users. I hope you could help me with this question about the function "ur.ers" in the package of "urca". It is an improved unit root test (Elliott et al. 1996 Econometrica). Do you know how to extract the value of the test statistic from the output? The only thing I can get is the print-out of all

Dear R Users, Could somebody please compare the packages of unit root test ( Uroot, Ucra, tseries and fseries ) regarding the type of test ( without constant and trend, with constant , and with constant and trend ) ? Regards, Amir Safari --------------------------------- Rekindle the Rivalries. Sign up for Fantasy Football [[alternative HTML version deleted]]

Dear R users, I have a function (below) which encompasses several tests. However, when I run it, only 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)

Hi, How can I access the Values stored in kpssstat-class given by KPSS.test function and store it in a variable. For example: >x <- rnorm(1000) >test <- KPSS.test(ts(x)) >test ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null

Dear R users, I have the joined txt file in the following direct directory C:// I have written the following lines: library(urca); PIBTUN<-read.table("C:/AF.txt", header=F); ur.df(PIBTUN,type='none',lags=1) but I have obtained the following message: Error in embed(z, lags) : 'x' is not a vector or matrix I don't What's the problem, can you please help me Thank

Hi All, First of all, could you tell me what the "KPSS Level" in the output of the test means? I have a series, x, of periodic data and tried kpss.test() on it to verify its stationarity. The tests gave me the p-value above 0.1. Since the null hypothesis N0 is that the series _is_ stationary, this means that I cannot reject N0. But the series does look periodic! So does all this

Situation: I had tired a 1000-data generated by random error(i.i.d.), then I sub it into different unit root tests. I got different results among the tests. The following are the test statistics I got: adf.test @ tseries ~ -10.2214 (lag = 9) ur.df @ urca ~ -21.8978 ur.sp @ urca ~ -27.68 pp.test @ tseries ~ -972.3343 (truncation lag =7) ur.pp @ urca ~ -973.2409 ur.kpss @ urca ~ 0.1867 kpss.test @

Dear R Core Team, I am using package {urca} to do cointegration and estimate ECM model, but I have the following two problems: (1) I use ca.jo() to do cointegration first and can get the cointegration rank, alpha and beta. The next step is to test some restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest(). But none of them can add restrictions on all the cointegration