similar to: Re: Artrage 3.5.4 on Ubuntu 11.10

Absolutely. I've just created a new entry (http://appdb.winehq.org/objectManager.php?sClass=version&iId=25122) considering AR3 v.3.5.4, which contains a note about this issue.

I installed Artrage Studio Pro 3.5.4 on Ubuntu 11.10. The installation went fine as long as the shortcut calls are unchecked. The program is launched automatically after installation and it works fine. However, I can't launch it afterwards. This is what I get. Code: wine "/home/anonymous/.wine/drive_c/Program Files/Ambient Design/ArtRage Studio Pro/ArtRage Studio Pro.exe"

Hello I want to fit an AR model were two of the coefficients are fixed to zero (the second and third ar-coefficients). I used the "arima" function with the "fixed" argument but the ar3 coefficient is not set to zero: ============================================== > arima(Y, order=c(4,0,0), xreg=1:23, fixed=c(NA,0,0,NA,NA,NA)) Call: arima(x = Y, order = c(4, 0, 0), xreg =

I'm using the fixed argument in arima. Shouldn't ar4, ar5, and ar6 display as zero in the output? Call: arima(x = window(log(hhprice), start = c(1990, 1), end = c(2003, 3)), order = c(7, 1, 0), xreg = window(ts.union(exa1 = lag(exa, -1), exa12 = lag(exa, -12), exb1 = lag(exb, -1), exc1 = lag(exc, -1), exc12 = lag(exc, -12)), start = c(1990, 1), end = c(2003, 3)),

Dear users, I tried to fit an AR(2) model to data. This the result: > arima(vw,c(3,0,0)) Call: arima(x = vw, order = c(3, 0, 0)) Coefficients: ar1 ar2 ar3 intercept 0.1052 -0.0102 -0.1203 0.0099 s.e. 0.0337 0.0339 0.0338 0.0018 sigma^2 estimated as 0.002934: log likelihood = 1293.16, aic = -2576.33 Now, ar2 is not significantly different from

Hello , I have estimated the following model, a sarima: p=9 d=1 q=2 P=0 D=1 Q=1 S=12 In R 2.12.2 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(reltol = tol)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 0.3152 0.8762 -0.4413 0.0152 0.1500 0.0001 -0.0413 -0.1811

Dear all, The standard call to ARIMA in the base package such as arima(y,c(5,0,0),include.mean=FALSE) gives a full 5th order lag polynomial model with for example coeffs Coefficients: ar1 ar2 ar3 ar4 ar5 0.4715 0.067 -0.1772 0.0256 -0.2550 s.e. 0.1421 0.158 0.1569 0.1602 0.1469 Is it possible (I doubt it but am

Hi, Can anyone explain how the standard error in arima() is calculated? Also, how can I extract it from the Arima object? I don't see it in there. > x <- rnorm(1000) > a <- arima(x, order = c(4, 0, 0)) > a Call: arima(x = x, order = c(4, 0, 0)) Coefficients: ar1 ar2 ar3 ar4 intercept -0.0451 0.0448 0.0139 -0.0688 0.0010 s.e.

Running the application ArtRage 2.11 which requires msvcr80.dll pops up the following error message : Runtime Error Program C:/...../Artrage.exe An application has made an attempt to load the C runtime library incorrectly. Searching around, I've found that there's a bug report about a similar error,for a different application and for wine version 0.9.10, but nothing else, concerning

hey can anybody help me? i have to simulate the richardson Arms race model on R.. for my simulation class...

Hi Jean-Marc, Sorry for late reply, thanks for interest. It's quality good for 10ms/audio, poorer for 20ms/audio. Quality equivalent for 10,20ms for mode=voip. PESQ was the tool that alerted me to something of interest, but I don't trust PESQ to almost any degree! It's good for hearing relative differences, of course, but not absolutes. Bitrate here was 28kbps, but I hear

Hello , I have estimated the following model, a sarima: p=9 d=1 q=2 P=0 D=1 Q=1 S=12 In R 2.12.2 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(reltol = tol)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 0.3152 0.8762 -0.4413 0.0152 0.1500 0.0001 -0.0413 -0.1811

Hi dear sirs, I am wondering why the fit of the time serie x with an arima and the fit of diff(x) with an arma (same coeff p & d) differ one from another here are the output of R: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% > modelarma<-arma(diff(x),c(7,5)) > modelarma Call: arma(x = diff(x), order = c(7, 5)) Coefficient(s): ar1 ar2 ar3 ar4 ar5 ar6 ar7 ma1 ma2 0.06078

Hi Kevin, Are you saying that the quality is good at 20 ms and bad at 10 ms, or the reverse? Also, is this speech or music? What tool, what options? In general, it helps a lot if you post the sample (input and output). Cheers, Jean-Marc On 06/03/2016 12:48 PM, Kevin Connor wrote: > Hi Opus list, > > I'm noticing a discontinuity in the quality between use of 10ms and > 20ms

Is it possible to fit a lagged regression, "y[t]=b0+b1*x[t-1]+e", using the function "lag"? If so, how? If not, of what use is the function "lag"? I get the same answer from y~x as y~lag(x), whether using lm or arima. I found it using y~c(NA, x[-length(x)])). Consider the following: > set.seed(1) > x <- rep(c(rep(0, 4), 9), len=9) > y <-

Hello, I'm running a number of arima models using the "arima" function. Often, when lag length gets too high, these model don't converge and an error message appears as this: > reg <- arima(y,order=c(7,0,7),xreg=isr) Warning message: In arima(y, order = c(7, 0, 7), xreg = isr) : possible convergence problem: optim gave code=1 In this case, when you print the results

Dear list and Martin, I'm testing different approaches to fit an electricity demand time series and come upon the fracdiff package (v 1.3-1) for fitting fractional ARIMA models. The following questions are motivated by this package. 1. Despite having a help page, the residuals and fitted functions don't seem to have implementation, or did i miss something obvious? Alternatively, having a

Good afternoon, I would like fitting an ARIMA model without the first coefficient. For example, I want to fit an AR(3) like this : y[t]=a[1]*y[t-1]+a[2]*y[t-2]+a[3]*y[t-3], where a[1]=0. How can I specify it in the function "arima", if it is possible ? Thank you in advance. Yohann Moreau [[alternative HTML version deleted]]

Hello R People: When using the arima function with the seasonal option, are the seasonal options only good for monthly and quarterly data, please? Also, I believe that weekly and daily data are not appropriate for seasonal parm estimation via arima. Is that correct, please? Thanks, Sincerely, Laura Holt mailto: lauraholt_983 at hotmail.com download!

The Wine development release 1.5.16 is now available. What's new in this release (see below for details): - New version of the Mono package. - Many improvements to the CMD command-line parser. - More stream classes in the C++ runtime. - Support for managing services in WMI. - Improved CPU detection. - Various bug fixes. The source is available from the following locations: