# rowQuantiles: Estimates quantiles for each row (column) in a matrix In matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors)

## Description

Estimates quantiles for each row (column) in a matrix.

## Usage

 1 2 3 4 5 rowQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, ..., drop = TRUE) colQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, ..., drop = TRUE)

## Arguments

 x An integer, numeric or logical NxK matrix with N >= 0. rows A vector indicating subset of rows to operate over. If NULL, no subsetting is done. cols A vector indicating subset of columns to operate over. If NULL, no subsetting is done. probs A numeric vector of J probabilities in [0, 1]. na.rm If TRUE, missing values are excluded. type An integer specify the type of estimator. See quantile for more details. ... Additional arguments passed to quantile. drop If TRUE, singleton dimensions in the result are dropped, otherwise not.

## Value

Returns a NxJ (KxJ) matrix, where N (K) is the number of rows (columns) for which the J quantiles are calculated. The return type is either integer or numeric depending on type.

Henrik Bengtsson

## Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 set.seed(1) x <- matrix(rnorm(50 * 40), nrow = 50, ncol = 40) str(x) probs <- c(0.25, 0.5, 0.75) # Row quantiles q <- rowQuantiles(x, probs = probs) print(q) q_0 <- apply(x, MARGIN = 1, FUN = quantile, probs = probs) stopifnot(all.equal(q_0, t(q))) # Column IQRs q <- colQuantiles(x, probs = probs) print(q) q_0 <- apply(x, MARGIN = 2, FUN = quantile, probs = probs) stopifnot(all.equal(q_0, t(q)))

### Example output

num [1:50, 1:40] -0.626 0.184 -0.836 1.595 0.33 ...
25%          50%       75%
[1,] -0.6218885  0.106762508 0.5512421
[2,] -0.3049272  0.056473676 0.7057890
[3,] -0.9231354 -0.118361292 0.7422711
[4,] -0.9322740 -0.207686499 0.3216682
[5,] -0.7084443 -0.035489532 0.6621024
[6,] -0.9664491 -0.216591179 0.6740367
[7,] -1.0384055  0.042690771 0.6611677
[8,] -0.6330825 -0.126332443 0.6960917
[9,] -1.0094086 -0.041113665 0.6791968
[10,] -0.6327419  0.054660577 0.6222087
[11,] -0.5645887 -0.041477859 0.3713240
[12,] -0.2766925  0.110955064 0.7428664
[13,] -0.8453155 -0.334769330 0.5554439
[14,] -0.8897809 -0.324080709 0.3301178
[15,] -0.7251620 -0.188349538 0.3535435
[16,] -0.4797823  0.091562203 0.9726725
[17,] -0.6200479 -0.262020284 0.6356199
[18,] -0.9034017 -0.140455912 0.7528919
[19,] -0.7707722 -0.152329236 0.1729031
[20,] -0.3200883  0.302574383 1.2132039
[21,] -0.5291880 -0.214782932 0.5513092
[22,] -0.5356002  0.284290389 0.7989148
[23,] -0.5700878  0.149494637 0.8077412
[24,] -0.7503936 -0.077770110 0.5309214
[25,] -0.4267110  0.263799916 0.7293052
[26,] -0.9591707 -0.137898692 0.3078452
[27,] -1.0171397 -0.150011032 0.6103426
[28,] -0.2687164  0.085033622 0.7435987
[29,] -0.7860127 -0.286445627 0.5151106
[30,] -0.3577578 -0.022684187 0.5654628
[31,] -0.9519151 -0.538929463 0.4145123
[32,] -0.6973686 -0.118983171 0.9168207
[33,] -0.8027962 -0.204718112 0.4979713
[34,] -0.9273236 -0.141973088 0.4361869
[35,] -0.4532102  0.365402869 0.7459632
[36,] -0.4184018  0.227594464 0.7615129
[37,] -0.6367977  0.088614257 0.9296158
[38,] -0.4039084 -0.010658183 0.7876346
[39,] -0.3561294  0.373172018 1.0347134
[40,] -0.7034831 -0.005856479 0.5258082
[41,] -0.6183522 -0.064312777 0.7153803
[42,] -0.4235112  0.125571403 0.6848875
[43,] -0.5556839  0.124678003 0.5593517
[44,] -0.5123758  0.439573098 0.8486753
[45,] -1.0042770 -0.060667550 0.9481150
[46,] -1.0340398 -0.310771412 0.1371124
[47,] -0.8865014  0.142643098 0.9203617
[48,] -0.7968222 -0.172298103 0.6482758
[49,] -1.2293839 -0.139233624 0.5217433
[50,] -0.6553804 -0.262142026 0.4742108
25%          50%       75%
[1,] -0.3720646  0.129104154 0.7279844
[2,] -0.5721162  0.113797331 0.6065313
[3,] -0.6469564 -0.246846356 0.2694256
[4,] -0.7041278 -0.055939482 0.8196898
[5,] -0.6089229 -0.029054330 0.6243079
[6,] -0.4185202  0.146116784 0.7594495
[7,] -0.4365107  0.091022110 0.8118479
[8,] -0.6197929 -0.032415219 0.6618606
[9,] -0.6727637 -0.273421020 0.6330157
[10,] -0.8825293 -0.011512761 0.5805665
[11,] -0.6381655  0.014950044 0.4831043
[12,] -0.7140804 -0.152388294 0.8106097
[13,] -0.7242296 -0.251628169 0.5387204
[14,] -1.0515879 -0.189977384 0.5571419
[15,] -0.9282411 -0.084192983 1.0093225
[16,] -0.8448598 -0.011103461 0.8216741
[17,] -0.5906504  0.161907795 0.7795111
[18,] -0.6499464 -0.059279451 0.5886333
[19,] -0.6094663  0.214748047 0.7317293
[20,] -0.7037132  0.022335956 0.5108679
[21,] -0.8504756  0.108484526 0.7602824
[22,] -0.7317770  0.007196516 0.7568682
[23,] -0.8515848 -0.319332762 0.5102586
[24,] -0.6366325 -0.249590203 0.6963329
[25,] -0.4791826  0.007958062 0.7657119
[26,] -0.4125492  0.291176656 1.0945407
[27,] -0.8272824 -0.267580711 0.3454911
[28,] -0.8544896 -0.197365516 0.4950755
[29,] -0.5364474  0.169648975 0.9752908
[30,] -0.6411633  0.057236706 0.5722226
[31,] -0.4458641 -0.018247105 0.7952345
[32,] -0.8358661  0.071609588 0.5724964
[33,] -0.5417449  0.124909830 0.5086025
[34,] -0.8415534 -0.215944585 0.5483784
[35,] -0.7080412 -0.017766239 1.0980467
[36,] -0.9491461 -0.256300105 0.4286593
[37,] -0.2463305  0.355645772 0.9952349
[38,] -0.5823101 -0.221579869 0.6592843
[39,] -0.8941790 -0.001721324 0.3406492
[40,] -0.6990172 -0.038793345 0.8817002

matrixStats documentation built on June 1, 2021, 9:09 a.m.