similar to: impulse response function

Hello, I'm doing a research on the impulse responses in VAR models and I'm having troubles in interpretation of R results. My question is what is the shock of impulse variable that is produced to obtain the response? Is it one-standard-deviation positive shock? If it is so how can I obtain the responses on other types of shocks, say, 10% negative shock? Thanks a lot, Marion

So I tried to run Impulse on my Ubuntu 11.04 laptop and it installed fine (or at least seemed to). When I tried to run it I got the working cursor for a bit then nothing. I ran it in terminal and got a error message about running the Windows version of Mono so I went online and did a search for the error message and found a file called mono-2.4.2.3-gtksharp-2.12.9-win32-3.exe and ran it. The error

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

Dear colleagues/contributors, I'd be pleased if someone could provide insights on how to plot impulse response functions in a format that can easily be copied in a word document just as plotting time-series of variables. I had followed the outline suggested by Benhard Pfaff [see http://127.0.0.1:17693/library/vars/html/irf.html] but I am unable to get the impulse response functions in a

I have been trying to get impulse (from stardock) to work in wine. I've managed to get it installed correctly by adding dotnet20 and gdiplus from winetricks. However, when I open impulse and try to log into my account, it always says that it cannot find the server and I should check my Internet correction. I've tried using StarDock Central (which I read works) but that has the same

Dear R users, I am using the vars package to calculate the impulse response functions and the forecast error variance decomposition of a VAR model. Unfortunately I do not know whether these functions assume unit or one standard deviation shocks. I tried to look into the code of these functions, but in vain: neither irf, nor vars::irf, nor vars:::irf output the code of the functions. Does someone

I am fitting a reduced form VAR model using VAR in the vars library. I have several endogenous variables, and two exogenous variables. I would like to explore the effects of a shock to one of the exogenous variables on one of the endogenous variables. Using irf in the vars library only calculates the irf for the endogenous variables, this is obviously by design, is there some theoretical

[message bounced because of "octet-stream" attachment which are not allowed in our mailing lists; manually fixed and approved, MM] Dear R-list, R: 1.5.1 OS: Windows NT additional packages needed: tseries for those of you who are interested, pls. find attached a function for estimating VECM's by employing the method of Johansen (see for example: Hamilton,

Hi, I made a small error in the impulse reponse function; when doing the inverse fft in fixed point, it will overflow unless it's properly scaled. This patch uses the same scaling as that used when updating the filters, and the outputs now have the same shape and the same scale in fixed and floating point. Best regards, Thorvald -------------- next part -------------- diff -ubBwr

Hi, I have the following C code. #define PTR_T char * typedef struct objcache { PTR_T data; int cs; /* cache size, number of objects */ int nc; /* number of cache entries */ } sh_obj_cache_t; struct dstack { char *delimiters; int delimiter_depth; int delimiter_space; }; When it is configured/made to generate IR with the following environment variables, CC=clang CXX=clang++

This has been bugging me for a while In php you can do $pVar++ to add 1 or $pVar-- to subtract, how can this be done in ruby? -- Posted via http://www.ruby-forum.com/.

All, Consider: BagA <- c(-1000,10,10,10,10,10,10, 10,20,20,20,20,20,20,30, 30,40,40,50,60) BagB <- c(10,20,30,30,40,40,50,50, 50,50,50,50,60,60,60,60, 60,60,60,1000) layout(c(2,1)) barplot(table(BagB)) barplot(table(BagA)) At this point, I'd like to arrange the plots so that the 10-bars are aligned, the 20-bars are aligned, etc. So, I started

Hi, I used RODBC to import data from an Excel spreadsheet "*.xls", but some columns were returned as zeros. When I looked at these columns in Excel, I found that thery are results of formula calculations and not entry. My question is: Is there any parameter or command I need to use in order to overcome this problem? Thank you Ahmad Abu Hammour

After playing with the vorbis code for a while and doing tons of hacks and analysis on it, I've found it to perform very poorly with impulse signals. The MDCT seems to cause lots of spreading, and it seems to result in much worse impulse performance then mp3. What is the current plan on handling this? Will a smart quantizer be able to avoid it? I've been looking at various ways of

Greetings all, I am getting this error that is driving me nuts... (not a long trip, haha) I have a set of files and in these files I want to calculate ttests on rows 'compareA' and 'compareB' (these will change over time there I want a variable here). Also these files are in many different directories so I want a way filter out the junk... Anyway I don't believe that this is

Hello, I want to know if there are some functions or packages to solve differential and integral equation using R. Thanks. Shao chunxuan. [[alternative HTML version deleted]]

Dear R useRs, i have the following code to compute values needed for a contour plot ############################################################ "myContour" <- function(a, b, plist, veca, vecb, dim) { tmpb <- seq(0.5 * b, 1.5 * b, length=dim) tmpa <- seq(0.5 * a, 1.5 * a, length=dim) z <- matrix(0, nrow=dim, ncol=dim) for(i in 1:dim) { for(j in 1:dim)

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<-

Full_Name: Ahmad Abu Hammour Version: rw0651 OS: windows 95 Submission from: (NULL) (63.23.128.44) Although I know that "ts package" is preliminary, I wanted to compare the results from R and SPSS. I ran ARIMA(2,1,2) in both softwares. I got NaN in standard errors of coefficients from R and real figures from SPSS. I changed "delta" in R to match that used by SPSS, I received

Hi, P-values in Durbin-Watson test obtained through the use of functions available in packages "lmtest" and "car" are different. The difference is quite significant. function "dwtest" in "lmtest" is much faster than "burbinwatson" in "car". Actually, you can take a nap while the latter trying to calculated Durbin-Watson test. My question