similar to: cointegration rank

Hello! I'm using the blrtest() function in the urca package to test cointegration relationships. Unfortunately, the hypothesis (restrictions on beta) specifies the same restriction on all cointegration vectors. Is there any possibility to specify different restrictions on the cointegration vectors? Are there any other packages in R using cointegration tests? Thanks and best regards. Dennis

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

Hello all, I would like to carry out a single-equation approach of the Error Correction Model such as Delta_y(t) = a + b*y(t-1) + c*x1(t-1) + d*x2(t-1) + e*delta_x1(t) + f*delta_x2(t) + epsilon(t) Where, a, b, c, d, e, f are coefficients to be estimated, y is the dependent variable, and x1, x2 are independent variables. For the single equation approach of ECM, there is a requirement of the

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

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

----- 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, 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")].

Frances, I would not advise Gauss-Seidel for non linear models. Can be quite tricky, slow and diverge. You can write your model as a non linear system of equations and use one of the nonlinear solvers. See the section "Root Finding" in the task view NumericalMathematics suggesting three packages (BB, nleqslv and ktsolve). These package are certainly able to handle medium sized models.

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 list subscriber, I am quite puzzled by the behaviour of processing Sweave files within an R session, i.e. Sweave("foo.Rnw") versus R CMD Sweave foo.Rnw In the former the environmental variable 'SWEAVE_STYLEPATH_DEFAULT = TRUE' is obeyed (this is set in etc/Renviron.site as well as under the users home directory in .Renviron). That is the hard-coded path to Sweave.sty is

> On 13 Jul 2017, at 12:55, Pfaff, Bernhard Dr. <Bernhard_Pfaff at fra.invesco.com> wrote: > > Who was speaking about non-linear models in the first place??? > The Klein-Model(s) and pretty much all simultaneous equation models encountered in macro-econometrics are linear That's really not true. Klein model is linear but Oseibonsu did not say that explicitly. "Klein

Folks, What is the best way to simulate values from a fitted "VAR {vars}" model. Also I have tried to use SVAR for a cointegration fit of y~x (just two univariate time-series) but I can't figure out how to set up the "A" matrix so that x_t can be used as a contemporaneous predictor of y_t. Thanks much for your time, KW -- [[alternative HTML version deleted]]

Dear R Core Team, I am using package {urca} to do cointegration and estimate ECM model, but I have the following two problems: (1) I use ca.jo() to do cointegration first and can get the cointegration rank, alpha and beta. The next step is to test some restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest(). But none of them can add restrictions on all the cointegration

Who was speaking about non-linear models in the first place??? The Klein-Model(s) and pretty much all simultaneous equation models encountered in macro-econometrics are linear and/or can contain linear approximations to non-linear relationships, e.g., production functions of the Cobb-Douglas type. Best, Bernhard -----Urspr?ngliche Nachricht----- Von: Berend Hasselman [mailto:bhh at xs4all.nl]

Dear list-member, I am currently developing a package with S4 classes. The NAMESPACE and DESCRIPTION is printed below. Within this package I have set a method "residuals" for two classes. In version 2.8.1 these two are reported whereas in R-Devel (2009-01-28 r47766). What have I missed? What has changed and how can I rectify the issue? Your help and pointers are welcome. For 2.8.1:

Hello, I tried to use urca package (R) for cointegration analysis. The data matrix to be investigated for cointegration contains 8 columns (variables). Both procedures, Phillips & Ouliaris test and Johansen's procedures give errors ("error in evaluating the argument 'object' in selecting a method for function 'summary'" respectiv "too many variables,

I am trying to run a conintegration analysis. I am a former user of S-Plus and understand the output of the coint and VECM output, but I am having trouble understanding the equivalent output in R. Here is what I ran > coint=ca.jo(data,constant=T,K=2,spec="longrun") > summary(coint) The first portion of the output that I did not understand [,1] [,2] [,3] y1

Dear list subscriber (R-Core), there is a minor typo in the Windows specific NEWS for R 2.9.0: http://cran.at.r-project.org/bin/windows/base/CHANGES.R-2.9.0 There is no function 'memory.limits() but memory.limit() (see below). Secondly, I am kind of irritated by the function's behaviour. It returns an Error, but as it seems the memory limit is set according to the numeric value for

Dear list subscriber, suppose, I do have a minimal Sweave file 'test.Rnw': \documentclass{article} \begin{document} <<printx>>= x @ \end{document} Within R, I define the following function: f <- function(x){ Sweave("test.Rnw") } The call: f(x = 1:10) results in the following error message: > f(x = 1:10) Writing to file test.tex Processing code chunks