search for: novum

Dear useRs, I have a curve which is a mixture of Gaussian curves (for example UV emission or absorption spectrum). Do you have any suggestions how to implement searching for optimal set of Gaussian peaks to fit the curve? I know that it is very complex problem, but maybe it is a possibility to do it? First supposement is to use a nls() with very large functions, and compare AIC value, but it is

Dear useRs, I need to compute zero of polynomial function fitted by lm. For example if I fit cubic equation by fit=lm(y~x+I(x^2)+i(x^3)) I can do it simply by polyroot(fit$coefficients). But, if I fit polynomial of higher order and optimize it by stepAIC, I get of course some coefficients removed. Then, if i have model y ~ I(x^2) + I(x^4) i cannot call polyroot in such way, because there is

Dear useRs, Is there any more elegant way to convert dataframe to a vector of all its values than as.vector(as.matrix(x)) ? I did not have to do such conversion yet, so I am not sure... (of course as.vector() alone does not work). Regards, -- Lukasz Komsta Department of Medicinal Chemistry Medical University of Lublin Jaczewskiego 4, 20-090 Lublin, Poland Fax +48 81 7425165

Dear useRs, I would like to summarize results of several tests in groups of two columns - statistic, p-value, statistic, p-value etc. There would be nice to add significance stars, but printCoefmat allows to do it only to last column. Is there any way to do format such table without writing my own complicated function? Thank you in advance, -- Lukasz Komsta Department of Medicinal

Dear useRs, I was searching CRAN for implementation of kurtosis and skewness tests, and found that there is some kind of lack on it. So, I have written three functions: 1. Anscombe-Glynn test for kurtosis 2. Bonett-Seier test based on Geary's kurtosis (which is not widely known, but I was inspired by original paper describing it, found coincidentally in Elsevier database) 3.