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...ed in the same way. They always start with results4$depth_ following by the number. The numbers are constructed as: seq(1,10,0.1). But if the R squared values are now in 1 column, I don?t know for which column they are calculated. So I made a new data frame with both columns: R2 <- unlist(LIST) Cvalue <- c(seq(1,10,0.1)) results5 <- data.frame(Cvalue,R2) # I know I can calculate the max value of Rsquared by this way: max(results5$R2) # now I want to know to which Cvalue this belongs. I would write it like this: results5$Cvalue[which(results5$R2 == "max(results5$R2)")] #...

Hello, I have a question concerning ?for loops? on multiple columns. I made 91 columns with results (all made together with a for loop) and I want to us lm to fit the model. I want to compare the results of all these calculated columns (91) with one column with observed values. I use the function lm to fit the model and calculate r.squared. I manage to do this for each column separately: For

...+ (1-par[i]*log(1-lambda[i]))); } return sum; } void optimgr(int n, double *par, double *gr, void *ex) { for(int i = 0; i < n; i++) { gr[i] = log(par[i]) - log(1-par[i]); } } void Test(SEXP SomeValues) { PROTECT(SomeValues = AS_NUMERIC(SomeValues)); double * CValues = NUMERIC_POINTER(SomeValues); void * optEx, *grEx, *overallEx; int mask = -1, fncount, grcount, failed; double *Fmax, *gradients; int size = sizeof(CValues)/sizeof(double); vmmin(size, CValues, Fmax, optimfn, optimgr,...

Well, it is clear enough that the problem is in interpreting the documentation. However, when you claim you tested something, and found it inconsistent with tables, it would be advisable to back it up with examples! The description in the help files and in the sources is admittedly confusing. The original paper has this, rather more clear, description in the abstract: "We consider the