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Dear Community, For my masters thesis I need to perform a multivariate granger causality test. I have found a code for bivariate testing on this page (http://www.econ.uiuc.edu/~econ472/granger.R.txt), which I think would not be useful for the multivariate case. Does anybody know a code for a multivariate granger causality test. Thank you in advance. Best Regards -- View this message in context: http://r.789695.n4.nabble.com/Multivariate-Granger-Causality-Tests-tp3332968p3332968...

I have a question regarding the adf.test command in the tseries library. I have a vector of time series observations (2265 daily log prices for the OEX to be exact). I also have this same data in first-differenced form. I want to test both vectors individually for staionarity with an Augmented Dickey-Fuller test. I noticed when I use the adf.test command from the tseries library, the general

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

Dear R users I have been looking for functions that can deal with overdispersed poisson models. Some (one) of the observations are negative. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. The presence of negatives is not