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Sorry to be off-topic. Can somebody please explain me what is Portmanteau test? Why it's name is like that? When I would say, a particular test is portmanteau test? I did some googling but got no satisfactory answer at all. Please anybody help for understanding that? Regards, -- View this message in context:

Hi, There's been quite a bit of interest and discussion for naming LLVM. So much so that I can't keep up with all the changes and ideas. We're working on getting a Wiki and CMS system running but its likely not to be available for a while. Until then, I'd like to change the rules for name submission: 1. If you have commit access, make the changes yourself. Please don't

Reid Spencer wrote: Reid, Seeing as we don't have a wiki, do you need help applying these patches? -- John T. > Hi, > > There's been quite a bit of interest and discussion for naming LLVM. So > much so that I can't keep up with all the changes and ideas. We're > working > on getting a Wiki and CMS system running but its likely not to be > available >

Dear Colleague I am trying to figure out how to use R to do OLS restricted VECM regression. However, there are some notation I cannot understand. Please tell me what is 'ect', 'sd' and 'LRM.dl1 in the following practice: #OLS retricted VECM regression data(denmark) sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")] sjd.vecm<-

Hello to everyone! I am working on my final year project about multivariate time series. There are three variables in the multivariate time series model. I have a few questions: 1. I used acf and pacf plot and find my variables are nonstationary. But in adf.test() and pp.test(), the data are stationary. why? 2.I use VAR to get a model. y is the matrix of data set and I have made a once

----- Forwarded Message ----- From: vramaiah at neo.tamu.edu To: "bernhard pfaff" <bernhard.pfaff at pfaffikus.de> Sent: Friday, November 11, 2011 9:03:11 AM GMT -06:00 US/Canada Central Subject: Use of R for VECM Hello Fellow R'ers I am a new user of R and I am applying it for solving Bi-Variate (Consumption and Output) VECM with Co-Integration (I(1)) with three lags on

Dear all, I have a question. How to get the standard errors of alpha and beta when using "ca.jo" to test cointergration? In the paper by Bernhard Pfaff and Kronberg im Taunus “VAR, SVAR and SVEC Models: Implementation Within R Package” pp.24-25. The standard errors are listed on the table 5 following the code: R> vecm.r1 <- cajorls(vecm, r = 1) I tried this in my Mac R, but

Dear All, My question is: how can I estimate VECM system with "unrestricted trend" (aka "case 5") option as a deterministic term? As far as I know, ca.jo in urca package allows for "restricted trend" only [vecm <- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K = n, spec = "transitory"/"longrun")].

Dear members, I estimated a vector error correction model (VECM) using the "ca.jo" function in package "urca". I need to simulate the estimated model using R. I am aware how to simulate a VAR(p) model. Since the VECM is in difference form, I can't modify the VAR simulation codes to VECM. May one help me in this regard please? Thanks Mamush [[alternative HTML version

Hello, I am currently testing a Vector AR of dim 3 over not a lot of data (135 * 3 observations) . To test the adequation of my vecot ar, I use the Schwarz Bayesian Criterion and the classic modified Portmanteau test on the residuals (it can be found for instance in http://www.iue.it/PUB/ECO2004-8.pdf , page 15) -> the null hypothesis is "the residuals process are a vectorila white

I don't like very much mithology or fantasy names. A portmanteau is more professional (even if it sounds funny). For now IMHO the best proposal is Omnipiler and OmniC, even if the last one reminds too much of C. Maybe Omnic (with the lowercase c), or Omnip are better. Simple, elegant and somehow reminds of something technological (to me at least :P). So my idea is to list some key words and

Dear R - helpers, I am using the urca package to estimate cointegration relations, and I would be really grateful if somebody could help me with this questions: After estimating the unrestriced VAR with "ca.jo" I would like to impose the rank restriction (for example rank = 1) and then obtain the restricted estimate of PI to be utilized to estimate the VECM model. Is it possible? It

I can't figure out how to get the "summary" method in the URCA package to work. E.g. when I use the following code fragment in the help for the "ca.jo" function, it always tries to use the "summary" method from the "base" package, not the "urca" package. How do I force it use the "summary" method of the "urca" package?

Hi all R users, I'm finding it a bit hard to interpret the output from the cajorls and VECM function. I'm trying to model a VECM model with cointegration rank of 6, and therefore I get the varibles ECT1, ECT2... ECT6 in my output. Are these representing the estimates for my loading matrix or also denoted the "alpha" matrix? Thanks in advanced Emil -- View this message in

Dear R users; I'm using ca.jo for a VECM model. Is there a way that I can get sd/p-value to see whether coefficients estimated are statistical significant? Thank you Yours, Yihsu [[alternative HTML version deleted]]

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

Add the 'label' optional argument to the mkfs action, so it is possible to set a filesystem label direct when creating it. There may be filesystems not supporting changing the label of existing filesystems but only setting it at creation time, so this new optarg will help. Implement it for the most common filesystems (ext*, fat, ntfs, btrfs, xfs), giving an error for all the others, just

Since mkfifo, mknod_b, and mknod_c add the correct file type to the modes of the resulting file, make sure the specified mode contains only permissions bits. --- daemon/mknod.c | 15 +++++++++++++++ generator/actions.ml | 21 ++++++++++++++++++--- 2 files changed, 33 insertions(+), 3 deletions(-) diff --git a/daemon/mknod.c b/daemon/mknod.c index 7f71210..9af8701 100644 ---

On 4/12/07, Chris Lattner <sabre at nondot.org> wrote: > Note that the name need not capture every aspect of the project. Just > having a distinguished name with no specific connotation is probably good > enough. 20 years ago, "google" and "yahoo" had very different meanings, > and "mozilla" or "firefox" were pretty meaningless. Today,

Hi, I am trying to estimate a VECM without constant using the following code: data(finland) sjf <- finland sjf.reg<-ca.jo(sjf, type = c("eigen"), ecdet = c("none"), K = 2,spec=c("transitory"), season = NULL, dumvar = NULL) cajools(sjf.reg) While the cointegration test does not use a constant, it is used in the cajools which I do not want. I am sure I am