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Dear list members, I have a statistical question, that doesn't belong to this list, and I apologise for that in advance but I would appreciate your help very much. Is there some convention for selecting the a level for significance testing in scientific (e.g. chemical processes) studies? Most people use the 0.05 level but I could not find a reference to justify this. Why not 0.01 or 0.1?

When I try to run the "sammon" function of the multiv package, I always get this error message: Error in as.vector(dist(a)) : couldn't find function "dist" It happens even with example(sammon). I am running R 1.5.0 on Win98 and I have still installed R 1.4.1 but it doesn't work on the old R version with the older multiv package either. Is there a problem with the

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking

Hello list members, I am new to this list and don't know very much about what R can do or how to program it, but I am interested in plotting 4 variables as sequential contour plots (or surface plots), something like the conditioning plots for 4 variables (coplot(X1~X2|X3+X4)). To be more specific, I need a tool that will automatically create contour (orsurface) plots of X1 vs X2 vs X3 for

Hello list members, this is rather a simple question but I can't find the solution myself, so I would appreciate your help and I apologise in advance for my ignorance. I have a data frame with a header containing variable names and I have 4 independent variables and 5 dependent variables. It looks like this: x1 x2 x3 x4 y1 y2 y3 y4 y5 1 1 33 55 4

Dear list members, I would like to ask two questions, although the second one must have been answered a thousand times. 1) is there a simple way to estimate the influence of individual variables in PCR and PLS models? What I have in mind is a way to rank the variables according to their influence, using some numerical value of a statistic. 2) what is the proper way to cite a CRAN package? How

Please, forgive my ignorance on statistics, but I have a rather simple question concerning AIC. Small values of AIC mean good fit of the model. How about negative values of AIC? Is a model with AIC=0.5 considered to have better fit than a model with AIC=-500? I couldn't find anything explaining this in the documentation or any elementary statistics textbook that I have at my disposal. Thanks

Dear list members, this is not an R question and forgive me for using the list for irrelevant questions, but this is the only place I know where I can find some good statisticians and I need an expert opinion. There is this power law kinetic model of the form: M=kt^n where t is the time, M is the fraction of drug released, k is the rate constant and n is an exponent related to the mechanism of