similar to: online classes or online eduction in statistics? esp. time series analysis and cointegration?

Hello! I am trying to duplicate the studentized bootstrap confidence interval calculations in boot.ci() without using boot.ci(). My w/o boot.ci() calculations are close to boot.ci() using the same object from implementation of boot(), but not quite the same (I think the differences are due to how quantiles are computed for z*). Through examining the boot.ci() code, I can see there is a call

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

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 looking for a package with which I can perform panel cointegration tests. Old threads suggest plm and urca package, but I don't find suitable tests in these packs. Somebody knows more? best regards, Philipp -- View this message in context: http://r.789695.n4.nabble.com/panel-cointegration-tp4593443p4593443.html Sent from the R help mailing list archive at Nabble.com.

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,

Dear folk, I am stempting to estimate a vector error correction model using a seemingly fractionally integrated multivariate time series. The *fracdiff *package provides tools to estimate degree of fractional integration. But *fracdiff *can't help me to: 1. test equality of two degrees of fractional integration, say d1=d2? 2. estimate a multivariate cointegrating error correction model,

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

Hi, Could someone please tell me the R codes for fitting VAR(p) (Vector Auto Regressive) models and doing the Johansen?s cointegration tests. TIA Aditya

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

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

Hello, I am using urca package to run cointegration. I would like to find the standard error in the (normalized, Johansen) cointegration relationship. How can I do it? As far as I know, The function "cajorls" in the "urca" package provides the normalized cointegrating relationships. Nevertheless, it does not provide the standard deviation of the coefficient for each

Hi, I am trying to test the cointegration among 5 time series, grouped in pairs. I would like to save in a table the cointegration vectors for the 10 tests. I used the urca package, but I dont know how to extract the data only for the cointegration vector. Thanks in advance for help ! Eduardo

Dear All, I am looking for a cointegration relationship between Spot and Future Price of commodites. The problem i am facing follows: 1. After estimating by Engle-Grranger Method, i found that the residuals are stationary at their level I (o), which is required to fulfill the cointegration test. But the autocorrelation problem arises, as DW statistics is signficantly low 0.50-0.88 for various

Hi everyone,   I'm trying to do an Logistic Politomic Regression in R. Because I have my resposes variables and the aswer is 0 and 1 in 3 bacterial genes. Somebody know how to do this in R in a easy way?   Thank so much,   José Bustos Facultad de Ciencias Universidad Catolica Ssma. Concepcion Chile --- El lun, 31/8/09, r-help-request@r-project.org <r-help-request@r-project..org>

Hi all R users, I'm trying to replicate the same results that are given in a published article after been granted the same data that the authors use. I'm having problems to determine the cointegration rank of my data set using the Johnasen's trace test. This trace test is already programmed in the package ur.ca and can be found in the function ca.jo(). After I run the ca.jo()

Dear Sir/Madam, I have used ca.jo in urca package to identify the cointegration and cajorls to estimate the vecm. Althought both return the coefficients for long run relationship (or ect1 in cajorls), I am unable to find the standard error and t statistics. I spend some weeks to search around. I did find some similar enquiries before and answer provided Prof. Pfaff is to use vec2var. However,

Hi, I have a couple of questions about johansen's test, in general: 1. I was able to obtain error correction term (ect) from cajorls$rlm$model properly. According the my ca.jo object on 2-variate series, the test suggests that the integration rank is 1. Which means that my ect should be stationary. However, I did test stationariy on ect and it shows non-stationarity and my acf still shows

Hi,I'm just wondering if there is any package for testing cointegration with ADL model. I saw a bunch of packages and list of email thread. There seemed to be no such a specific method. I am following this paper on how to test using ADL but I don't have a tool. http://www.wiwi.uni-frankfurt.de/~hassler/ha-wo.pdfAny help would be really appreciated. Thank you.Taco [[alternative HTML

Hello!   I estimate vector error correction model (vecm) model. I have only one cointegratio relationship. I write :   joh.vecm.rls <- cajorls(joh.vecm, r=1) The output estimation is : Call: lm(formula = substitute(form1), data = data.mat) Coefficients:                up.d            expl.d        upd.d           r.d      ect1      -1.34e-01   4.55e+02   6.91e+00   2.43e+03 constant 

Hello to all- 1. When I run a regression which implements the augmented Dickey-Fuller test, I am confused about the names given to the regressors in the output. I understand what "xGE" stands for in a standard "lm" test involving an independent variable GE for instance, but if I lags and or differences are included in the model, what do the following "output" stand