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Hi all, I think this question could be quite trivial, but I can?t find out the solution... How can you compute the statistic "mode" of a sample, in case it exists (as mode() returns the mode of an object)? I tried help.search("mode") but I couldn't find a clue... Any help would be much appreciated. Regards, Aurora

...I thought I'd run this idea by the list, and test it for feasibility. the basic idea follows: Most broadband users are on cable modems, which unfortunately limit up-stream bandwidth to a fraction of what many DSL users get to experience (I know the technical issues the cable companies always taut, however, I've always thought of it as a way to limit personal publishing ability). As such, a P2P radio broadcast network could not use the upstream of such users, putting the burden of distribution on a few, and thereby defeating the major point of the whole thing P2P in the first place. If...

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such

Hi, I was recently plowing through the docs of the quantreg package by Roger Koenker and came across the total variation penalty approach to 1-dimensional spline fitting. I googled around a bit and have found some papers originated in the image processing community, but (apart from Roger's papers) no paper that would discuss its statistical aspects. I have a couple of questions in this