similar to: Fixing an only one coefficient in an ARIMA model

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 , 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

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 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

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

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

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.

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!

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 Jonathan and Andrew, > Reminder of my original LDAP query: > (& > (objectCategory=Person) > (sAMAccountName=*) > (memberOf:1.2.840.113556.1.4.1941:=CN=mygroup,OU=myou,DC=mydomain,DC=org) > ) I came across the same/similar issue yesterday and found the origin that triggered the issue (at least in my case). I've added a response to your bugzilla entry

Dear R People: I have the output from an arima model fit in an object xxx. I want to verify that the ma1 coefficient is there, so I did the following: > xxx$coef ar1 ar2 ma1 intercept 1.3841297 -0.4985667 -0.9999996 -0.1091657 > str(xxx$coef) Named num [1:4] 1.384 -0.499 -1 -0.109 - attr(*, "names")= chr [1:4] "ar1" "ar2"

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

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, On Samba 3.0.2a on debian stable with a 2.6.5 kernel, each time I use APW to configure my printers, smbd takes more and more memory and the kernel does an Out of Memory (I have 512 Mo RAM). It's Xerox printers. Is the problem known (and corrected in 3.0.3rc1) or is it new ? Thanks for the answer. Cordialy, -- Yohann F.

Hi everyone, ----------------------------- Coefficients: ar1 ar2 ma1 ma2 sar1 intercept drift 1.5283 -0.7189 -1.9971 0.9999 0.3982 0.0288 -9e-04 s.e. 0.0869 0.0835 0.0627 0.0627 0.1305 NaN NaN sigma^2 estimated as 0.04383: log likelihood = 4.34, aic = 7.32 Warning message: NaNs produced in: sqrt(diag(object$var.coef))

I'm trying to use the following command. arima (x, order = c(p,d,q), seasonal =list(order=c(P,D,Q), period=s) How can I write an estimated seasonal ARIMA model from the outputs. To be specifically, which sign to use? I know R uses a different signs from S plus. Is it correct that the model is: (1-ar1*B-ar2*B^2-...)(1-sar1*B^s-sar2*B^2s-....)(1-B)^d(1-B^s)^D

Dear all, I have a problem that may be someone of you can help. I am a newbie and do not find how to do it in manuals. I have two arrays, for example: ar1 <- array(data=c(1:16),dim=c(4,4)) ar2 <- array(data=c(1:16),dim=c(4,4)) colnames(ar1)<-c("A","B","D","E") colnames(ar2)<-c("C","A","E","B") > ar1

Hello R users, Hope everyone is doing great. I have a dataset that is in .csv format and consists of two columns: one named Period (which contains dates in the format yyyy_mm) and goes from 1995_10 to 2007_09 and the second column named pcumsdry which is a volumetric measure and has been formatted as numeric without any commas or decimals. I imported the dataset as pauldataset and made use of

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