Have you searched?! "Granger causality" at rseek.org brought up what appeared to be many relevant hits.
-- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Jan 2, 2017 at 10:20 PM, PWD7052 via R-help <r-help@r-project.org> wrote: > Hi Everyone, > > We have a question about whether one can to do a particular type of Granger > Causality (GC) network validation in R. We hope you'll agree it's an > interesting problem and that someone's figured out how to solve it. > > We have a cellular network with n nodes (proteins). We have two different n > x s x k time series matrices that describe the network activity under two > mutually exclusive conditions, C (cancerous cell) and H (healthy cell), where > s is the length of the time series data, and k is the number of observations. > Using the time series matrices, we calculated two different n x n GC > matrices, one for healthy cells and one for cancerous cells, so that ij th > element in each matrix represents the GC influence of node i on node j. > Using the various standard tests, we know that many of the GC values are > extremely significant. > Now we’re given a brand-new observation in the form of a n x s x 1 time > series matrix Y that represents the activity of the same n nodes (we don’t > know a priori whether the new data come from a healthy cell or a cancerous > cell). > Given this matrix Y : > (1) How can we go about determining if Y comes from a cancerous cell > (condition C) or a healthy cell (condition H)? > (2) Is there a package in R that we can use for this purpose? > > Thank you very much! > Pat > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
