On Fri, Oct 8, 2010 at 11:35 AM, epowell <epowe...@med.miami.edu> wrote: > > My data looks like this: > >> data > name G_hat_0_0 G_hat_1_0 G_hat_2_0 G_0 G_hat_0_1 G_hat_1_1 G_hat_2_1 G_1 > 1 rs0 0.488000 0.448625 0.063375 1 0.480875 0.454500 0.064625 1 > 2 rs1 0.002375 0.955375 0.042250 1 0.000000 0.062875 0.937125 2 > 3 rs2 0.050375 0.835875 0.113750 1 0.877250 0.115875 0.006875 0 > 4 rs3 0.000000 0.074750 0.925250 2 0.897750 0.102000 0.000250 0 > 5 rs4 0.000125 0.052375 0.947500 2 0.261500 0.724125 0.014375 1 > 6 rs5 0.003750 0.092125 0.904125 2 0.023000 0.738125 0.238875 1 > > And my task is: > For each individual (X) on each row, to find the index corresponding to the > max of G_hat_X_0, G_hat_X_1, G_hat_X_2 and then increment the cell of the > confusion matrix with the row corresponding to that index and the column > corresponding to G_X. > > For example, in the first row and the first individual, the index with the > max value (0.488000) is 0 and the G_0 value is 1, so I would increment > matrix index of the first row and second column. (Note that the ranges > between rows and columns are one off. That is accounted for in the code.) > > In reality the data will be much bigger, containing 10000 rows and a > variable number of columns (inds) between 10 and 500. > > The correct result is: > >> cmat > tru_rr tru_rv tru_vv > call_rr 2 2 0 > call_rv 0 4 0 > call_vv 0 0 4 >
If we reform data into a 3d array, arr, it can be vectorized like this where the two args of table correspond to Gmax and Gtru: arr <- array(t(data[-1]), c(4, 2, 6)) table(apply(arr[-4,,], 2:3, which.max), arr[4,,] + 1) -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
