Is package:igraph loaded in your R session on the mac? Is it up to date? (I would doubt that is.dag would be a recently written function.)
Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com From: Dustin Fife [mailto:fife.dus...@gmail.com] Sent: Tuesday, January 29, 2013 9:16 AM To: William Dunlap Cc: Duncan Murdoch; r-help Subject: Re: [R] identify non-recursive models That looks like exactly what I need. I tested it on my PC and it ran, but my mac couldn't find the function "is.dag." Any ideas? On Tue, Jan 29, 2013 at 11:03 AM, William Dunlap <wdun...@tibco.com<mailto:wdun...@tibco.com>> wrote: is.dag()? Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com<http://tibco.com> > -----Original Message----- > From: r-help-boun...@r-project.org<mailto:r-help-boun...@r-project.org> > [mailto:r-help-boun...@r-project.org<mailto:r-help-boun...@r-project.org>] On > Behalf > Of Dustin Fife > Sent: Tuesday, January 29, 2013 8:52 AM > To: Duncan Murdoch > Cc: r-help > Subject: Re: [R] identify non-recursive models > > Thanks for the response. That doesn't seem to do it. It's able to identify > if one edge connects back into itself, but isn't able to identify whether > an edge eventually connects back into itself (after passing through > multiple variables). For example, the following should fail, because the > path goes from 1-2-3, then back into 1: > > is.simple(graph(c(1,2,2,3,3,1,3,4))) > > But, it returns TRUE. > > On Tue, Jan 29, 2013 at 10:21 AM, Duncan Murdoch > <murdoch.dun...@gmail.com<mailto:murdoch.dun...@gmail.com>>wrote: > > > On 29/01/2013 11:12 AM, Dustin Fife wrote: > > > >> Hi, > >> > >> I'm working on a project that will generate RAM matrices at random. What I > >> want to do is to be able to automatically identify if the model is > >> non-recursive. For example, the following RAM matrix has a non-recursive > >> loop (going from A to B to C to A): > >> > > > > I'm not familiar with your terms, but your description sounds like you > > want a test for a simple graph. I believe the igraph package has that in > > the "is.simple" function (and a lot of other tests of graph properties in > > case that's not the one you want). > > > > Duncan Murdoch > > > > > >> n.recursive <- data.frame(matrix(c("A", "B", 1, > >> "B", "C", 1, > >> "C", "A", 1, > >> "B", "D", 1), nrow=4, byrow=TRUE)) > >> names(n.recursive) <- c("From", "To", "Arrows") > >> > >> What I want to be able to do is have a function that automatically checks > >> whether there is a non-recursive path. Here's what I've thought of so far: > >> > >> 1. Find all variables that both send and receive an arrow. (in this case, > >> A > >> and B both fit that criteria). > >> > >> vars <- LETTERS[1:5] > >> double.arrow.vars <- vars[which(vars %in% n.recursive$From & vars %in% > >> n.recursive$To)] > >> > >> 2. For all variables found in #1, follow all paths exiting that variable > >> to > >> other variables, then follow all paths exiting that next variable > >> variable, > >> etc. and continue tracing the path. > >> > >> ##### insert complicated code here > >> > >> 3. If a variable is repeated, identify it as non-recursive. > >> > >> The problem with #2 is that, for large models, the number of paths to be > >> traced could be really large. (Also, I'm having trouble thinking of how to > >> code it so it's not really awkward). > >> > >> So, my question is this: is there a better way to approach the problem? Is > >> there a more efficient way? > >> > >> I know that I could probably identify which models are non-recursive after > >> estimation (via convergence failures or negative parameter estimates). But > >> I want to be able to identify them before estimation. Any help would be > >> appreciated. > >> > >> Dustin > >> > >> > >> > >> > >> > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org<mailto:R-help@r-project.org> mailing list > 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. -- Dustin Fife PhD Student Quantitative Psychology University of Oklahoma [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list 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.
