similar to: Complex demodulation - Purely a time series question

Here are another three problems with logarithmic scales: 1) segments() does not work with logarithmic scales. I suggest to change lines 962-973 in "plot.c": for (i = 0; i < n; i++) { if (FINITE(xt(x0[i%nx0])) && FINITE(yt(y0[i%ny0])) && FINITE(xt(x1[i%nx1])) && FINITE(yt(y1[i%ny1]))) { GP->col = INTEGER(col)[i % ncol];

Dave, I have been interested in some of the same questions that you have been asking. A while back I asked a person at VLSI ( http://www.vlsi.fi/ ) in Finland if they had a product that might work. The exchange of email is included below. In summary, the answer was probably no, but maybe in the future. The VS1005 chip he mentions does not seem to have appeared yet. I currently have a pair

"contour" can't return a list of contours (it would be nice) "arrows" has different options from S-PLUS (no "open" or "rel" options, no "lwd" parameter or graphics parameter pass-through; "size" in S corresponds to "length" in R). [I know we needn't follow S-PLUS syntax slavishly, but it would be nice at least to

Hi all, Can I run a cointegrating regression, for example delta Xt=a1(Yt-1-cXt-1)+E1t and delta Yt=-b1(Yt-1-cXt-1)+E2t with R were Xt and Yt are non stationary time series at t a,b,c are parameters and E1t and E2t are error terms at t. Yt-Xt is stationary Any suggestions are welcome. Best regards, /fb -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Hi all, I want to estimate parameters from a VARMA(p,q)-Modell. The equations of the model or the model structures is given by: Xt=beta1+beta2*Xt-1+beta3*Yt-1+epsilon1 Yt=beta4+beta5*Yt-1+espilon2 epsilon1 and espilon2 are white noise. Xt is given by a vector of n elements e.g. (2, 4, 7, 9, …,n)’ and Yt is given by a vector of n elements e.g. (4,9,12,17,…,n)’. The lineVar from

Dermot MacSweeney pointed out to me that after my "fix" of legend(), points were no longer coming out placed in the middle of the lines, but at the right-hand edge. It turns out that naively swapping the order of point-drawing and line-drawing also messes up the bookkeeping that legend() does on the current x-location. Here's my patch, which fixes that bookkeeping (and incidentally

Perhaps I should have submitted this as a bug so that it would be officially tracked. It's not a big deal, but here it is again (I can't remember which version this patch is against, but I don't think legend() has changed since then ...) Basically, the problem is that if you want to have "opaque" points that overlay lines (rather than using type="b" and having

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

Dear R users, I am trying to carry out MLE of the time-varying CAPM using the FKF package. My approach so far has been to try and adapt the example given in the help file found using ?fkf which demonstrates the MLE of an ARMA(2,1) model. When I attempt to run my R code (given below) I get the following error: Error in fkf(a0 = sp$a0, P0 = sp$P0, dt = sp$dt, ct = sp$ct, Tt = sp$Tt, : Some of

when we applied box priece Q statistic in stat library how does it work? suppose we have series Yt then either it apply on residuals obtained by regressing yt on Yt-1 .or apply direct on the series Yt --------------------------------- [[alternative HTML version deleted]]

Dear R users, I hope this mailing list be the right place for my question. Usaully performance criterion of curve fitting like as Directinal Symmetry (DS) and Mean Absolute Percentage Error (MAPE) are correctly used with absolute time series which includes only positive values. But how it is possible to use DS and MAPE with other time series like as return series (for example return of a

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

Le 31/05/2017 ? 17:30, Serguei Sokol a ?crit : > > More thorough reading revealed that I have overlooked this phrase in the > line's doc: "left and right /thirds/ of the data" (emphasis is mine). Oops. I have read the first ref returned by google and it happened to be tibco's doc, not the R's one. The layout is very similar hence my mistake. The latter does not

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Hello all, * * I'm having some difficulty, and I think the problem is with how I'm using append() nested inside a for loop. The data are: y,x 237537.61,873 5007.148438,227 17705.77306,400 12396.64369,427 228703.4021,1173 350181.9752,1538 59967.79376,630 140322.7774,710 42650.07251,630 5382.858702,264 34405.82429,637 92261.34614,980 144927.1713,1094 362998.7355,1420 203313.6442,1070

I have made a minor hack to "legend" (in R 1.0.0, but I didn't notice any changes to legend in the 1.0.1 NEWS) to allow the legend to be formatted in multiple columns, or horizontally (number of columns <- number of legend items). (I find this helpful when I have lots of legend items and not a lot of vertical space to squeeze the legend into.) (Another hack I've considered

Hey, I have a few doubts with regard to the usage of the auto.arima function from the forecast package in R. *Background:* I have a set of about 50 time-series for which I would like to estimate the best autroregressive model. (I want to estimate the coefficients and order of p). Each of the series is non-stationary and are also have a non-normal distribution. The data is non-seasonal. My

Dear R-Users I think I am getting the hang of how sweave works. However there is one thing I am struggling with - nice small size graphics. Here is the piece of the Rnw file that creates the figures. <<pl1,fig=TRUE,include=FALSE,echo=false>>= #pdf(file="datapl1.pdf",paper="a4",width=0,height=0); plot(yt,ypred,xlab="Data",ylab="Predicted

Hello, Please copy all replies directly to me (my account is having difficulty with receiving lists these days). This is primarily a programming question, but the specifics regard start values for a nonlinear regression (if you have suggestions on alternative ways to obtain start values they are welcome as well). I'm using nls to estimate a nonlinear time series equation of the form:

http://bugs.freedesktop.org/show_bug.cgi?id=24328 Summary: swfdec crashing in both firefox and epiphany Product: swfdec Version: unspecified Platform: Other OS/Version: All Status: NEW Severity: normal Priority: medium Component: plugin AssignedTo: swfdec at lists.freedesktop.org