similar to: Compare two time series, at each time step

Hi R-users, I'm trying to produce decompositions of a multiple time-series, grouped by a factor (called "area"). I'm modifying the code in the STLperArea function of package ndvits, as this function only plots produces stl plots, it does not return the underlying data. I want to extract the trend component of each decomposition ("x$time.series[,trend]), assign a name

Hi, I have a irregularly spaced time series dataset, which reads in from a .csv. I need to convert this to a regularly spaced time series by filling in missing rows of data with NAs. So my data, called NtuMot, looks like this (I've removed some of the additional rows for simplicity).... ELEID date_time height slope 1 2009-06-24 00:00:00

Hello, I have conducted an SEM in which the resultant standardized path coefficients are much higher than would be expected from the raw correlation matrix. To explore further, I stripped the model down to a simple bivariate relationship between two variables (NDVI, and species richness), where it's my understanding that the SEM's standardized path coefficient should equal the correlation

Hi, I?m trying to use the STLperArea function in the ndvits package. I can run the sample data (?SLPSAs_full?) without any problem. However, when I come to run the function on my own data, I get the following message. Waiting to confirm page change... Error in .checkPath(path) : no TISEAN executables found in that directory. Please set a proper TISEAN executables path using

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

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

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

I have two samba servers running Ubuntu 10.04 Samba Version 3.4.7 One server acts as domain controller and stores user ids in a .tdb Somehow I've ended up with a duplicate user name. On the Domain Controller # pdbedit -w -L|grep debbie debbie:1005:XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX:84DEC6FE3B018B0FB977EDDF5009742C:[U ]:LCT-4D4B086F: On the other Server running winbind I get #

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

The patch prevents KEIL MDK compile warnings, like:   warning:  #1035-d: single-precision operand implicitly converted to double-precision Actually ARM Cortex-M4F has only a *single precision* (float) FPU. It's suit for all platforms. See the comment at the begin of patch file. Sincerely Forrest Zhang -------------- next part -------------- Specify the floating point constant with single

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,

Top posting... While I don't really see any details that indicate this is the problem, systemd-resolved causes the packaged 18.04 samba to fail to start [at least in a full AD setup.] That's because system has a full DNS resolver, and Samba also has it's own DNS resolver. When they both try to start on the same port, the first running wins [systemd] and Samba exits. Since you're

Hi All, I'm running into a problem with GAM (in the MGCV package). When I try to estimate the model, I get the following error message: 1> fit <- gam(ndvi~s(rain)+s(temp)+s(rainl1)+s(rainl2)+s(rainxY)+s(rainl1xY)+s(rainl2xY)+s(tempxY), data=dsub, weights=wvec) Error in while (mean(ldxx/(ldxx + ldss)) > 0.4) { : missing value where TRUE/FALSE needed Using

On Sun, 24 Feb 2019 13:08:07 -0500 Robert Steinmetz <rob at steinmetznet.com> wrote: > Rowland Penny via samba wrote: > On Sat, 23 Feb 2019 19:55:03 -0500 > Robert Steinmetz via samba <samba at lists.samba.org> wrote: > > I ungraded my Linux Operating system from Ubuntu 16.04 LTS to 8.04 LTS > > Samba will not start after an upgrade to 18.04. My samba is running

Hello R-users, I'm currently facing a pretty hard problem which I'm hopping you'll be able to help me with. I'm using R to create images. That alone is not the problem, the problem is that I'm using R to create 168 000 images... My code (which is given below) use different package (raster and rgdal) to import a image (size 20gig) and divide it into 168 000 pictures that are

Hi, I am performing GEV analysis on temperature/precipitation data and want to use the ks.boot function but I am unsure of how to implement it using the pgev distribution. For example: ks.test(data,pgev,shape,location,scale) ks.boot(data,(distribution parameters?),alternative="pgev",nboots=1000) Any advice? Apologies in advance if I have used the wrong email address. Regards, Louise

Thanks for the response. I think  found and fixed the problem, but I need to do some more testing tomorrow. It seems that the "handle_name_resolve_order: WARNING: Ignoring invalid list value 'hosts'  for parameter 'name resolve order'" is not really a warning and it causes testparm to stop processing the smb.conf. I think that is also what caused the daemons to fail.

Dear all, I have been working in a plot based on figure 5.6 of the Lattice book (http://lmdvr.r-forge.r-project.org/figures/figures.html). I have already modified it to include the size of the circles as another variable, but I would like to modify the legend to show it (like they do it in http://www.jstatsoft.org/v15/i05/paper). I have divided my variable in intervals: DATA$s_Shape_2 <-

I ungraded my Linux Operating system from Ubuntu 16.04 LTS to 8.04 LTS Samba will not start after an upgrade to 18.04. My samba is running as an NT style member server server with smbd nmbd and winbindd all running. None of them will start. It worked this morning. This morning it was running Version 4.3.11-Ubuntu This afternoon after the upgrade it's Version 4.7.6-Ubuntu The logs in

Hi weekend R helpers, *Is it possible to get a ylabel on the right hand side axis ==> axis(4)? Thankx, Jan opar <- par(mfrow = c(2,1)) plot(ts.Origi[,1],ylab='NDII', main=name) # Add the legend text in the right order legend.txt <- c("NDII", "Inverse KBDI") legend(2001.8,0.29, legend.txt,col=c(1,2), lty=1)