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Hi all, I've got object *cumsumtab, *where the first row (1,2,3,4,5,6,8,13,14,17,40) are names (actually, categories), and the second row has numeric values. > cumsumtab 1 2 3 4 5 6 8 13 14 17 40 2 4 6 7 9 11 13 14 15 16 17 I'm trying to find a way of finding to which category ( in *names(cumsumtab) * ) belongs a given value (let's say Q1 <- 4.25). So far, I've

Hi all... I built a matrix binding vectors with rbind, and have something like this: [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] CLS 3.877328 4.087636 4.72089 4.038361 3.402942 2.786285 2.671222 3.276419 ORD NaN NaN NaN NaN 5.770780 5.901113 11.888054 7.934823 FAM NaN NaN NaN NaN NaN 3.699455 4.551196 2.885390 GEN

Hi all, I''ve got a simple contingency table produced with table(), and the upper and lower quartiles (quantile25 and quantile75) for the same dataset. Is there a function that tells me in which category does the value of the quartile falls into? for example: tabsp <- table(fam$I[fam$I>0]) 1 3 6 6 1 1 and for the cumulative frequency distribution tabcum <- cumsum(tabsp) 1 3

Hi all, I can't compute the sum by columns to a matrix using apply() when I've got missing values (either 0 or NA)... I've got this matrix: >nafam Micro Flavo Helio Pseud Rhodo Bdello Chloro Syntro Verruco Prochloro SAR11 I 1 1 1 NA NA 1 3 NA 1 6 1 VII NA 1 2 1 NA 2 16 1 NA 12 35 XI