similar to: Creating symbolic expressions in R

Hello, I'm trying to convert a vector of string objects to a numeric object by initializing the variables with values. I use the function below to scan through a matrix and create mass action flux relationships: makeMassActionFluxes = function(sMatrix) { #Allocate a matrix with identical dimensions as the inputted stoichiometric matrix temp = matrix(nrow = dim(sMatrix)[1], ncol =

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

Greetings, If this is not the appropriate place to post this question please let me know where to post it. I have a package under development which fits models of the form $$ f(t)=\sum_i B_iG_i(t,\omega) $$ depending on a parameter vector $\omega$ of arbitrary dimension to data (one dimensional time series) in the general framework of the data = deterministic signal + Gaussian noise in the

Had a nasty memory leak that was seriously slowing down the browser and eating up a couple megabytes every reload. I was using: $$(''.dyntable'').each(function(elm) { new DynTable(elm) }); To set up my behavior, but discovered that just running: $$(''.dyntable''); Caused the memory leak all by itself. The fix I found for it was to change Element.extend to a

Hello, I am using the mda package and in particular the fda routine to classify in term of gear a set of 20 trips. I preformed a flexible discriminant analysis (FDA) using a set of 151 trips. FDAT1 <- fda(as.factor(gear) ~ . , data =matrizR) A total of 22 predictors were considered. 20 of the predictors are "numeric" and 2 are "factors/discrete". The resulting FDA