search for: stationar

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 0.574 0.739 ---- Statistic for the null hypothesis of trend stationarity: 0...

Does anyone know of a test for stationarity of a time series, or like all ordination techniques it is a qualitative assessment of a quantitative result. Books, papers, etc. suggestions welcome. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for...

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 hypothesis of level stationarity: 0.138 Critical values: 0.10 0.05 0.025 0.01 0.347 0.463 0.574 0.739 ---- Statistic for the null hypothesis of trend stationarity: 0...

Hi all, Could anybody tell me how to test for stationarity in time series? Thanks a lot! [[alternative HTML version deleted]]

Dear R list members, Please excuse my ignorance but as a new comer to R I was wondering if anyone knows of any functions in R or Splus that can test a time-series for non-stationarity such as the Pettitt or the Mann-Kendall tests. Kind regards, Jon Nott [[alternative HTML version deleted]]

How can I make sure the residual signal, after subtracting the trend extracted through some technique, is actually trend-free ? I would greatly appreciate any suggestion about some Stationarity tests. I'd like to make sure I have got the difference between ACF and PACF right. In the following I am citing some definitions. I would appreciate your thoughts. ACF(k) estimates the correlation between y(t) and y(t-k) like an ordinary correlation coefficient. ACF is the simple ( i.e. u...

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...

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 say stationarity and periodicity can co-exist? Thanks, Weiguang

Hi there, Does anyone know if R has a function for testing whether a time series is stationary?? Thanks in advance, Wayne Dr Wayne R. Jones Statistician / Research Analyst KSS Group plc St James's Buildings 79 Oxford Street Manchester M1 6SS Tel: +44(0)161 609 4084 Mob: +44(0)7810 523 713 KSS Ltd A division of Knowledge Support Systems Group plc Seventh Floor St James's Bui...

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...

This is not exactly an R question but the R code below may make my question more understandable. If one plots sin(x) where x runs from -pi to pi , then the curve hovers around zero obviously. so , in a"stationary in the mean" sense, the series is stationary. But, clearly if one plots the acf, the autocorrelations at lower lags are quite high and, in the "box jenkins" sense, this series is clearly not stationary in terms of its acf. so, i'm confused in terms of what ithe statistical de...

How to find out if EURGBP is stationary? Post the R codes for the same.

...ing a, I use the following codes result1 = arima(ts(myinput),order = c(p,d,q),seasonal = list(order=c(P,D,Q))) result2 = forecast(result1,12) plot(result2) Now, by using R code... 1) How can I determine if my data is statitonary or not ? (trend & seasonal effects) 2) If not, how can I make it stationary ? 3) Is arima() function used only on STATIONARY data ? Or does it first determine if the data is stationary or not and makes it stationary ? (if it is non-stationary) 4) I tried different parameter values in arima() function, but every parameter gave very different results :(( . I even found &amp...

...f (tonal->highE[b] > tonal->lowE[b] + 7.5f) { if (tonal->highE[b] - logE[b] > logE[b] - tonal->lowE[b]) tonal->highE[b] -= .01f; @@ -700,7 +700,7 @@ static void tonality_analysis(TonalityAn L2 += tonal->E[i][b]; } - stationarity = MIN16(0.99f,L1/(float)sqrt(1e-15+NB_FRAMES*L2)); + stationarity = MIN16(0.99f,L1/(float)sqrt(1e-15f+NB_FRAMES*L2)); stationarity *= stationarity; stationarity *= stationarity; frame_stationarity += stationarity; @@ -748,7 +748,7 @@ static void tonality_analysis(To...

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 &l...

...z-score p-value Z-Score p-value b[1] 1.143 0.253 0.000 1.000 b[2] 0.470 0.638 0.056 0.956 b[3] -1.037 0.300 -0.388 0.698 b[4] -0.618 0.536 -0.085 0.933 tau -0.206 0.837 -0.008 0.994 sigma 0.716 0.474 0.437 0.662 CODA -- Heidelberger and Welch Stationarity start p-value test iteration b[1] passed 1 0.2649 b[2] passed 1 0.6709 b[3] passed 1 0.6376 b[4] passed 1 0.3673 tau passed 1 0.1944 sigma passed 1 0.0725 Halfwidth Mean Halfwidt...

...276, 313, 292, 302, 322, 281, 298, 305, 295, 286, 327, 286, 270, 289, 293, 287, 267, 267, 288, 304, 273, 264, 254, 263, 265, 278) x <- ts(x, frequency = 12) library (urca) library (uroot) library (tseries) Now, doing an ur.kpss test (mu, lag=3) i cannot reject the null hypothesis of level stationarity. Doing a kpss.test (mu, lag=1 by default ) the p value becomes smaller than 0.05 thus rejecting the null of stationarity. Same with KPSS.test (lag=1) So, as i have noticed that increasing the number of lags on each of the tests rejecting the null becomes harder and harder. I saw that books alwa...

Can someone explain to me in what way the new (dpqr)gamma parameter can be interpreted as a rate (when shape != 1)? The only gamma rate that I am aware of is the hazard rate given by dgamma/(1-pgamma), the log of which is returned by my hgamma function (event library). Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi I am thinking of ripping albums to a single flac file with embedded cuesheet. As track and index points have to be on a 588 sample boundary due to the CD TOC standard working in 588 sample frames, I thought it may be beneficial to rip CDs with a blocksize of 588 samples. According to the format page on sourcefourge a stream is subset if "The blocksize bits in the frame header must be

hello R experts, my question is regarding arma modelling and specification. in another older, statistics package , after determining stationarity, i would try to work out the number of ar and ma lags using an lm test. to do this i would 1. regress my dependant variable on an intercept term then 2. use LM test for serial correlation, and finally 3. use the p value of the ols residuals to get the maximum lags for the arma specification....